vecId stringlengths 12 23 | id stringlengths 2 13 | conference stringclasses 11
values | year float64 2.02k 2.03k | title stringlengths 6 189 | abstract stringlengths 10 4.74k | author stringlengths 0 7.45k | aff stringlengths 0 7.16k | status stringclasses 11
values | track stringclasses 4
values | keywords stringlengths 0 804 | github stringlengths 0 141 | site stringlengths 0 193 | gsCitation float64 -1 11.1k | arxiv stringlengths 0 12 | text stringlengths 58 4.82k | vector list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
wacv_2025_b5925d1a46 | b5925d1a46 | wacv | 2,025 | Self-Aligning Depth-Regularized Radiance Fields for Asynchronous RGB-D Sequences | It has been shown that learning radiance fields with depth rendering and depth supervision can effectively promote the quality and convergence of view synthesis. However this paradigm requires input RGB-D sequences to be synchronized. In the UAV city modeling scenario there exists asynchrony between RGB images and dept... | Yuxin Huang; Andong Yang; Yuantao Chen; Runyi Yang; Zhenxin Zhu; Chao Hou; Hao Zhao; Guyue Zhou | ;;;;;;; | Poster | main | github.com/saythe17/AsyncNeRF | https://openaccess.thecvf.com/content/WACV2025/html/Huang_Self-Aligning_Depth-Regularized_Radiance_Fields_for_Asynchronous_RGB-D_Sequences_WACV_2025_paper.html | 0 | Self-Aligning Depth-Regularized Radiance Fields for Asynchronous RGB-D Sequences
It has been shown that learning radiance fields with depth rendering and depth supervision can effectively promote the quality and convergence of view synthesis. However this paradigm requires input RGB-D sequences to be synchronized. In t... | [
-0.051964666694402695,
-0.010441324673593044,
-0.013614668510854244,
-0.025870662182569504,
-0.005811593029648066,
0.03052365779876709,
0.041355833411216736,
0.05598485469818115,
0.006458359304815531,
0.06882712990045547,
-0.0278435330837965,
-0.0077705043368041515,
0.021478231996297836,
0... | ||
wacv_2025_1e66576298 | 1e66576298 | wacv | 2,025 | Self-Relaxed Joint Training: Sample Selection for Severity Estimation with Ordinal Noisy Labels | Severity level estimation is a crucial task in medical image diagnosis. However accurately assigning severity class labels to individual images is very costly and challenging. Consequently the attached labels tend to be noisy. In this paper we propose a new framework for training with "ordinal" noisy labels. Since seve... | Shumpei Takezaki; Kiyohito Tanaka; Seiichi Uchida | Kyushu University, Fukuoka, Japan; Kyoto Second Red Cross Hospital, Kyoto, Japan; Kyushu University, Fukuoka, Japan | Poster | main | https://github.com/shumpei-takezaki/Self-Relaxed-Joint-Training | https://openaccess.thecvf.com/content/WACV2025/html/Takezaki_Self-Relaxed_Joint_Training_Sample_Selection_for_Severity_Estimation_with_Ordinal_WACV_2025_paper.html | 0 | 2410.21885 | Self-Relaxed Joint Training: Sample Selection for Severity Estimation with Ordinal Noisy Labels
Severity level estimation is a crucial task in medical image diagnosis. However accurately assigning severity class labels to individual images is very costly and challenging. Consequently the attached labels tend to be nois... | [
-0.05616394802927971,
-0.011714835651218891,
-0.05687393620610237,
-0.003542943624779582,
0.0038395512383431196,
-0.014040987007319927,
0.02711040899157524,
0.006497343070805073,
0.032958485186100006,
0.015619780868291855,
-0.010332223027944565,
0.012835872359573841,
0.001372102415189147,
... | |
wacv_2025_6bec36f5ea | 6bec36f5ea | wacv | 2,025 | Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet | A robust anomaly detection mechanism should possess the capability to effectively remediate anomalies restoring them to a healthy state while preserving essential healthy information. Despite the efficacy of existing generative models in learning the underlying distribution of healthy reference data they face primary c... | Komal Kumar; Snehashis Chakraborty; Dwarikanath Mahapatra; Behzad Bozorgtabar; Sudipta Roy | Artificial Intelligence & Data Science, Jio Institute, Navi Mumbai, India; Artificial Intelligence & Data Science, Jio Institute, Navi Mumbai, India; Faculty of IT, Monash University, Australia; Swiss Federal Institute of Technology Lausanne (EPFL) University Hospital Center (CHUV), Lausanne, Switzerland; Artificial In... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kumar_Self-Supervised_Anomaly_Segmentation_via_Diffusion_Models_with_Dynamic_Transformer_UNet_WACV_2025_paper.html | 0 | Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet
A robust anomaly detection mechanism should possess the capability to effectively remediate anomalies restoring them to a healthy state while preserving essential healthy information. Despite the efficacy of existing generative mode... | [
-0.05550609901547432,
-0.0027739328797906637,
-0.0270029678940773,
0.019776564091444016,
-0.010729837231338024,
0.0119189927354455,
0.00045508050243370235,
0.01789220981299877,
0.0011657150462269783,
0.045041535049676895,
-0.030058180913329124,
0.01316303201019764,
-0.03649791330099106,
0.... | |||
wacv_2025_0cb1ca4ca4 | 0cb1ca4ca4 | wacv | 2,025 | Self-Supervised Incremental Learning of Object Representations from Arbitrary Image Sets | Computing a comprehensive and robust visual representation of an arbitrary object or category of objects is a complex problem. The difficulty increases when one starts from a set of uncalibrated images obtained from different sources. We propose a self-supervised approach Multi-Image Latent Embedding (MILE) which compu... | George Leotescu; Alin-Ionut Popa; Diana-Nicoleta N Grigore; Daniel Voinea; Pietro Perona | Amazon Inc.+California Institute of Technology; Amazon Inc.+California Institute of Technology; Amazon Inc.+California Institute of Technology; Amazon Inc.+California Institute of Technology; Amazon Inc.+California Institute of Technology | Poster | main | https://github.com/amazon-science/mile | https://openaccess.thecvf.com/content/WACV2025/html/Leotescu_Self-Supervised_Incremental_Learning_of_Object_Representations_from_Arbitrary_Image_Sets_WACV_2025_paper.html | 0 | Self-Supervised Incremental Learning of Object Representations from Arbitrary Image Sets
Computing a comprehensive and robust visual representation of an arbitrary object or category of objects is a complex problem. The difficulty increases when one starts from a set of uncalibrated images obtained from different sourc... | [
-0.061113398522138596,
-0.02809702605009079,
-0.019166523590683937,
0.032202787697315216,
-0.010113037191331387,
-0.01708526350557804,
0.03218386694788933,
0.020907215774059296,
-0.0032921768724918365,
0.012298361398279667,
-0.021853242069482803,
-0.00717562111094594,
0.0010471345158293843,
... | ||
wacv_2025_30034d9c9c | 30034d9c9c | wacv | 2,025 | Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation | Numerical weather prediction (NWP) models are fundamental in meteorology for simulating and forecasting the behavior of various atmospheric variables. The accuracy of precipitation forecasts and the acquisition of sufficient lead time are crucial for preventing hazardous weather events. However the performance of NWP m... | Junha Lee; Sojung An; Sujeong You; Namik Cho | Seoul National University; Korea Institute of Atmospheric Prediction Systems; Korea Institute of Industrial Technology; Seoul National University | Poster | main | https://github.com/joonha425/SSLPDL | https://openaccess.thecvf.com/content/WACV2025/html/Lee_Self-Supervised_Learning_with_Probabilistic_Density_Labeling_for_Rainfall_Probability_Estimation_WACV_2025_paper.html | 0 | 2412.05825 | Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation
Numerical weather prediction (NWP) models are fundamental in meteorology for simulating and forecasting the behavior of various atmospheric variables. The accuracy of precipitation forecasts and the acquisition of sufficien... | [
-0.1264614462852478,
0.013788117095828056,
-0.0053931549191474915,
0.0033185116481035948,
-0.04817579314112663,
-0.02961415797472,
0.0013471412239596248,
-0.01548638753592968,
-0.02190309390425682,
0.01516509335488081,
-0.0071006049402058125,
-0.0054482342675328255,
-0.008661177940666676,
... | |
wacv_2025_30c42b28d6 | 30c42b28d6 | wacv | 2,025 | Self-Supervised Learning with Spectral Low-Rank Prior for Hyperspectral Image Reconstruction | Hyperspectral image (HSI) reconstruction from coded measurement is significant for acquiring images with higher spectral resolution than traditional RGB images. Current advanced neural networks have already shown impressive performance in some datasets like CAVE and KAIST. However these networks rely on a large amount ... | Zijun He; Lishun Wang; Ziyi Meng; Xin Yuan | Zhejiang University+Westlake University; Westlake University; Westlake Intelligent Vision; Westlake University | Poster | main | https://github.com/zjhe02/CASSI-SSL | https://openaccess.thecvf.com/content/WACV2025/html/He_Self-Supervised_Learning_with_Spectral_Low-Rank_Prior_for_Hyperspectral_Image_Reconstruction_WACV_2025_paper.html | 0 | Self-Supervised Learning with Spectral Low-Rank Prior for Hyperspectral Image Reconstruction
Hyperspectral image (HSI) reconstruction from coded measurement is significant for acquiring images with higher spectral resolution than traditional RGB images. Current advanced neural networks have already shown impressive per... | [
-0.05025099962949753,
-0.009350944310426712,
0.00025837833527475595,
-0.007153151091188192,
-0.006354787852615118,
-0.017958583310246468,
0.04757143557071686,
0.001933966064825654,
-0.021932046860456467,
0.02585962787270546,
-0.05737203359603882,
-0.033916670829057693,
0.00818092841655016,
... | ||
wacv_2025_10c2c16499 | 10c2c16499 | wacv | 2,025 | Self-Supervised Pre-Training with Diffusion Model for Few-Shot Landmark Detection in X-Ray Images | Deep neural networks have been extensively applied in the medical domain for various tasks including image classification segmentation and landmark detection. However their application is often hindered by data scarcity both in terms of available annotations and images. This study introduces a novel application of deno... | Roberto Di Via; Francesca Odone; Vito Paolo Pastore | MaLGa, DIBRIS, University of Genoa, Italy; MaLGa, DIBRIS, University of Genoa, Italy; MaLGa, DIBRIS, University of Genoa, Italy | Poster | main | https://github.com/Malga-Vision/DiffusionXray-FewShot-LandmarkDetection | https://openaccess.thecvf.com/content/WACV2025/html/Di_Via_Self-Supervised_Pre-Training_with_Diffusion_Model_for_Few-Shot_Landmark_Detection_in_WACV_2025_paper.html | 2 | Self-Supervised Pre-Training with Diffusion Model for Few-Shot Landmark Detection in X-Ray Images
Deep neural networks have been extensively applied in the medical domain for various tasks including image classification segmentation and landmark detection. However their application is often hindered by data scarcity bo... | [
-0.07316341996192932,
-0.03018530085682869,
-0.02499270997941494,
0.020518817007541656,
-0.017185857519507408,
0.00708815548568964,
0.023411575704813004,
0.034784965217113495,
0.021668734028935432,
0.01169680431485176,
-0.040750157088041306,
-0.028298718854784966,
0.0005440765526145697,
0.... | ||
wacv_2025_03283df41b | 03283df41b | wacv | 2,025 | Semantic Clustering of Image Retrieval Databases used for Visual Localization | Accurate self-localization of unmanned aerial systems (UAS) is needed to reduce their dependency on global navigation satellite systems (GNSS). Image retrieval techniques comparing aerial images with a reference database can be used for visual localization (VL). But the search space may be vast and a full search not fe... | Henry Hölzemann; Torsten Fiolka | Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE; Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Holzemann_Semantic_Clustering_of_Image_Retrieval_Databases_used_for_Visual_Localization_WACV_2025_paper.html | 0 | Semantic Clustering of Image Retrieval Databases used for Visual Localization
Accurate self-localization of unmanned aerial systems (UAS) is needed to reduce their dependency on global navigation satellite systems (GNSS). Image retrieval techniques comparing aerial images with a reference database can be used for visua... | [
-0.03596636652946472,
0.015606469474732876,
-0.024695543572306633,
0.020907655358314514,
-0.025809628888964653,
0.012013547122478485,
0.04166676849126816,
0.014678065665066242,
0.021408993750810623,
0.019793571904301643,
-0.014752338640391827,
-0.018113160505890846,
0.012245647609233856,
0... | |||
wacv_2025_e35f209911 | e35f209911 | wacv | 2,025 | Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation | Weakly-Supervised Semantic Segmentation (WSSS) aims to train segmentation models using image data with only image-level supervision. Since precise pixel-level annotations are not accessible existing methods typically focus on producing pseudo masks for training segmentation models by refining CAM-like heatmaps. However... | Ci-Siang Lin; Chien-Yi Wang; Yu-Chiang Frank Wang; Min-Hung Chen | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lin_Semantic_Prompt_Learning_for_Weakly-Supervised_Semantic_Segmentation_WACV_2025_paper.html | 0 | 2401.11791 | Semantic Prompt Learning for Weakly-Supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation (WSSS) aims to train segmentation models using image data with only image-level supervision. Since precise pixel-level annotations are not accessible existing methods typically focus on producing pseudo masks fo... | [
-0.07099427282810211,
-0.0011898793745785952,
-0.013378586620092392,
-0.0014630031073465943,
-0.006554970517754555,
-0.038434334099292755,
0.01912761852145195,
-0.0013465897645801306,
-0.0013868866953998804,
0.0333479642868042,
-0.004746085032820702,
-0.005234126001596451,
0.0007410161197185... | ||
wacv_2025_9ad3809afa | 9ad3809afa | wacv | 2,025 | Semantic Prompting with Image Token for Continual Learning | Continual learning aims to refine model parameters for new tasks while retaining knowledge from previous tasks. Recently prompt-based learning has emerged to leverage pre-trained models to be prompted to learn subsequent tasks without the reliance on the rehearsal buffer. Although this approach has demonstrated outstan... | Jisu Han; Jaemin Na; Wonjun Hwang | ;; | Poster | main | https://github.com/pilsHan/I-Prompt | https://openaccess.thecvf.com/content/WACV2025/html/Han_Semantic_Prompting_with_Image_Token_for_Continual_Learning_WACV_2025_paper.html | 2 | 2403.11537 | Semantic Prompting with Image Token for Continual Learning
Continual learning aims to refine model parameters for new tasks while retaining knowledge from previous tasks. Recently prompt-based learning has emerged to leverage pre-trained models to be prompted to learn subsequent tasks without the reliance on the rehear... | [
-0.08296941220760345,
-0.032828304916620255,
-0.015322932042181492,
0.009756792336702347,
0.002158369403332472,
-0.026189284399151802,
0.004580373875796795,
0.003778005950152874,
-0.012223499827086926,
-0.014460960403084755,
-0.033525217324495316,
-0.04126463085412979,
-0.010417026467621326,... | |
wacv_2025_4208a67211 | 4208a67211 | wacv | 2,025 | Semantic Segmentation Method for Automated Indoor 3D Reconstruction Based on Architectural-Knowledge-Aware Features | 3D point cloud semantic segmentation is an important step for 3D indoors reconstruction. In recent years many outstanding deep learning models have been proposed for semantic segmentation which can achieve remarkable performance. However it is found the index indicating semantic prediction accuracy in terms of structur... | Yahan Chen; Wenzheng Liu; Xiaowei Luo | ;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Chen_Semantic_Segmentation_Method_for_Automated_Indoor_3D_Reconstruction_Based_on_WACV_2025_paper.html | 0 | Semantic Segmentation Method for Automated Indoor 3D Reconstruction Based on Architectural-Knowledge-Aware Features
3D point cloud semantic segmentation is an important step for 3D indoors reconstruction. In recent years many outstanding deep learning models have been proposed for semantic segmentation which can achiev... | [
0.0077786631882190704,
-0.02262226864695549,
-0.03151216730475426,
-0.008975728414952755,
0.013118023984134197,
-0.004085830878466368,
0.05330326780676842,
0.0016555633628740907,
0.00548391230404377,
0.015466981567442417,
-0.022423509508371353,
0.021375512704253197,
-0.0008435919298790395,
... | |||
wacv_2025_0c4dc24d98 | 0c4dc24d98 | wacv | 2,025 | Semantically Conditioned Prompts for Visual Recognition under Missing Modality Scenarios | This paper tackles the domain of multimodal prompting for visual recognition specifically when dealing with missing modalities through multimodal Transformers. It presents two main contributions: (i) we introduce a novel prompt learning module which is designed to produce sample-specific prompts and (ii) we show that m... | Vittorio Pipoli; Federico Bolelli; Sara Sarto; Marcella Cornia; Lorenzo Baraldi; Costantino Grana; Rita Cucchiara; Elisa Ficarra | University of Modena and Reggio Emilia, Italy + University of Pisa, Italy; University of Modena and Reggio Emilia, Italy; University of Modena and Reggio Emilia, Italy; University of Modena and Reggio Emilia, Italy; University of Modena and Reggio Emilia, Italy; University of Modena and Reggio Emilia, Italy; University... | Poster | main | https://github.com/vittoriopipoli/SCP_WACV2025 | https://openaccess.thecvf.com/content/WACV2025/html/Pipoli_Semantically_Conditioned_Prompts_for_Visual_Recognition_under_Missing_Modality_Scenarios_WACV_2025_paper.html | 0 | Semantically Conditioned Prompts for Visual Recognition under Missing Modality Scenarios
This paper tackles the domain of multimodal prompting for visual recognition specifically when dealing with missing modalities through multimodal Transformers. It presents two main contributions: (i) we introduce a novel prompt lea... | [
-0.05647933855652809,
-0.029304295778274536,
0.008422277867794037,
0.0277885552495718,
-0.021400796249508858,
-0.01889260858297348,
0.02017376944422722,
0.009365104138851166,
0.03666645660996437,
0.005070509389042854,
-0.006820827256888151,
-0.04576089605689049,
0.011386089958250523,
0.037... | ||
wacv_2025_1efd8399b4 | 1efd8399b4 | wacv | 2,025 | Semiotic-Based Construction of a Large Emotional Image Dataset with Neutral Samples | Image Visual Sentiment Analysis (VSA) requires the availability of large annotated datasets whose construction presents many challenges. The necessity of gathering a large amount of labeled images contrasts with the rigorous but lengthy process required for manual annotation based on psychovisual experiments and with t... | Marco Blanchini; Giovanna Dimitri; Lydia Abady; Benedetta Tondi; Tarcisio Lancioni; Mauro Barni | University of Siena, Italy; University of Siena, Italy; University of Siena, Italy; University of Siena, Italy; University of Siena, Italy; University of Siena, Italy | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Blanchini_Semiotic-Based_Construction_of_a_Large_Emotional_Image_Dataset_with_Neutral_WACV_2025_paper.html | 0 | Semiotic-Based Construction of a Large Emotional Image Dataset with Neutral Samples
Image Visual Sentiment Analysis (VSA) requires the availability of large annotated datasets whose construction presents many challenges. The necessity of gathering a large amount of labeled images contrasts with the rigorous but lengthy... | [
-0.09179585427045822,
-0.054955728352069855,
-0.015308824367821217,
0.035032372921705246,
-0.004643074236810207,
-0.01952374540269375,
0.027344660833477974,
0.03769643232226372,
0.004507492296397686,
0.00744985044002533,
-0.0035726933274418116,
0.005061711650341749,
0.016003381460905075,
0... | |||
wacv_2025_8e33b5f31d | 8e33b5f31d | wacv | 2,025 | SenCLIP: Enhancing Zero-Shot Land-Use Mapping for Sentinel-2 with Ground-Level Prompting | Pre-trained vision-language models (VLMs) such as CLIP demonstrate impressive zero-shot classification capabilities with free-form prompts and even show some generalization in specialized domains. However their performance on satellite imagery is limited due to the under representation of such data in their training se... | Pallavi Jain; Dino Ienco; Roberto Interdonato; Tristan Berchoux; Diego Marcos | Mediterranean Agronomic Institute of Montpellier - CIHEAM-IAMM+Inria+Univ. of Montpellier; Inria+INRAE+UMR TETIS+Univ. of Montpellier; Inria+Cirad+UMR TETIS+Univ. of Montpellier; Mediterranean Agronomic Institute of Montpellier - CIHEAM-IAMM; Inria+Univ. of Montpellier | Poster | main | https://github.com/pallavijain-pj/SenCLIP | https://openaccess.thecvf.com/content/WACV2025/html/Jain_SenCLIP_Enhancing_Zero-Shot_Land-Use_Mapping_for_Sentinel-2_with_Ground-Level_Prompting_WACV_2025_paper.html | 4 | SenCLIP: Enhancing Zero-Shot Land-Use Mapping for Sentinel-2 with Ground-Level Prompting
Pre-trained vision-language models (VLMs) such as CLIP demonstrate impressive zero-shot classification capabilities with free-form prompts and even show some generalization in specialized domains. However their performance on satel... | [
-0.08976687490940094,
0.011439803056418896,
-0.00756723852828145,
-0.01185944490134716,
0.0010593677870929241,
-0.0212740208953619,
-0.0047711459919810295,
0.02503255195915699,
-0.022605927661061287,
0.014915533363819122,
-0.0055100806057453156,
-0.0025155707262456417,
0.004570447839796543,
... | ||
wacv_2025_065d977b7d | 065d977b7d | wacv | 2,025 | SensorFlow: Sensor and Image Fused Video Stabilization | We present SensorFlow a novel image and sensor fusion framework for robust high-quality video stabilization. We start with sensor-based pre-stabilization that smooths out large-scale camera motion. A new angular velocity domain optimization has been introduced to achieve frame rate invariance. We then feed the stabiliz... | Jiyang Yu; Tianhao Zhang; Fuhao Shi; Lei He; Chia-Kai Liang | Google; Google; Google; Google; Google | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yu_SensorFlow_Sensor_and_Image_Fused_Video_Stabilization_WACV_2025_paper.html | 0 | SensorFlow: Sensor and Image Fused Video Stabilization
We present SensorFlow a novel image and sensor fusion framework for robust high-quality video stabilization. We start with sensor-based pre-stabilization that smooths out large-scale camera motion. A new angular velocity domain optimization has been introduced to a... | [
-0.05850336328148842,
-0.01208463590592146,
-0.023427315056324005,
-0.015618209727108479,
0.0017157772090286016,
0.003160275984555483,
-0.03129206597805023,
0.03943505138158798,
0.03928666189312935,
0.0327945314347744,
0.017500927671790123,
-0.026691928505897522,
0.026729026809334755,
0.01... | |||
wacv_2025_4d65e68cd2 | 4d65e68cd2 | wacv | 2,025 | Separating Direct and Global Components from Novel Viewpoints | Separating an image of a scene illuminated by a light source into direct components such as specular reflection and diffuse reflection and global components such as inter-reflection and subsurface scattering is important as preprocessing for various computer vision and graphics applications. Conventional methods cannot... | Kengo Matsufuji; Lin Shi; Ryo Kawahara; Takahiro Okabe | Kyushu Institute of Technology*; Kyushu Institute of Technology†; Kyoto University‡; Okayama University§ | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Matsufuji_Separating_Direct_and_Global_Components_from_Novel_Viewpoints_WACV_2025_paper.html | 0 | Separating Direct and Global Components from Novel Viewpoints
Separating an image of a scene illuminated by a light source into direct components such as specular reflection and diffuse reflection and global components such as inter-reflection and subsurface scattering is important as preprocessing for various computer... | [
-0.011237566359341145,
0.0026204087771475315,
0.00043673478648997843,
0.01404926273971796,
-0.007047678343951702,
-0.029094142839312553,
0.02568323351442814,
0.02496417611837387,
0.028670083731412888,
0.024871990084648132,
-0.01601284183561802,
-0.0028462663758546114,
-0.010269605554640293,
... | |||
wacv_2025_603d0c0193 | 603d0c0193 | wacv | 2,025 | Shadow Removal Refinement via Material-Consistent Shadow Edges | Shadow boundaries can be confused with material boundaries as both exhibit sharp changes in luminance or contrast within a scene. However shadows do not modify the intrinsic color or texture of surfaces. Therefore on both sides of shadow edges traversing regions with the same material the original color and texture sho... | Shilin Hu; Hieu Le; ShahRukh Athar; Sagnik Das; Dimitris Samaras | ;;;; | Poster | main | https://github.com/cvlab-stonybrook/ShadowRemovalRefine | https://openaccess.thecvf.com/content/WACV2025/html/Hu_Shadow_Removal_Refinement_via_Material-Consistent_Shadow_Edges_WACV_2025_paper.html | 0 | 2409.06848 | Shadow Removal Refinement via Material-Consistent Shadow Edges
Shadow boundaries can be confused with material boundaries as both exhibit sharp changes in luminance or contrast within a scene. However shadows do not modify the intrinsic color or texture of surfaces. Therefore on both sides of shadow edges traversing re... | [
-0.037576824426651,
-0.002596191829070449,
-0.05897294729948044,
-0.024621205404400826,
-0.016484782099723816,
-0.020198233425617218,
0.010670416988432407,
0.053075652569532394,
0.014641876332461834,
0.031992822885513306,
-0.015157890506088734,
-0.01490909792482853,
-0.025984954088926315,
... | |
wacv_2025_572d3a048a | 572d3a048a | wacv | 2,025 | Shape-Biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation | Recent advances in machine learning have greatly benefited object detection and 6D pose estimation. However textureless and metallic objects still pose a significant challenge due to few visual cues and the texture bias of CNNs. To address this issue we propose a strategy for inducing a shape bias to CNN training. In p... | Peter Hönig; Stefan Thalhammer; Jean-Baptiste Weibel; Matthias Hirschmanner; Markus Vincze | TU Wien, Austria; UAS Technikum Vienna, Austria; TU Wien, Austria; TU Wien, Austria; TU Wien, Austria | Poster | main | https://github.com/hoenigpeter/randomized_texturing | https://openaccess.thecvf.com/content/WACV2025/html/Honig_Shape-Biased_Texture_Agnostic_Representations_for_Improved_Textureless_and_Metallic_Object_WACV_2025_paper.html | 0 | Shape-Biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation
Recent advances in machine learning have greatly benefited object detection and 6D pose estimation. However textureless and metallic objects still pose a significant challenge due to few visual cu... | [
-0.05114622786641121,
-0.022457139566540718,
-0.02738001011312008,
0.009725895710289478,
0.006333355791866779,
-0.004881385713815689,
0.004667046945542097,
0.04546741023659706,
0.018880221992731094,
0.037188876420259476,
-0.004487279336899519,
-0.049191828817129135,
0.004968964494764805,
0... | ||
wacv_2025_6207511fff | 6207511fff | wacv | 2,025 | ShapeMorph: 3D Shape Completion via Blockwise Discrete Diffusion | We introduce ShapeMorph a diffusion-based method specifically designed for generating precise and diverse 3D shape completions. By integrating an irregular discrete representation with a novel blockwise discrete diffusion model ShapeMorph can produce multiple high-quality shape completions while maintaining fidelity to... | Jiahui Li; Pourya Shamsolmoali; Yue Lu; Masoumeh Zareapoor | East China Normal University; East China Normal University; East China Normal University; Shanghai Jiao Tong University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Li_ShapeMorph_3D_Shape_Completion_via_Blockwise_Discrete_Diffusion_WACV_2025_paper.html | 0 | ShapeMorph: 3D Shape Completion via Blockwise Discrete Diffusion
We introduce ShapeMorph a diffusion-based method specifically designed for generating precise and diverse 3D shape completions. By integrating an irregular discrete representation with a novel blockwise discrete diffusion model ShapeMorph can produce mult... | [
-0.011980381794273853,
-0.01907750591635704,
0.0020430423319339752,
-0.005015361588448286,
-0.01330141257494688,
-0.012936990708112717,
0.024452734738588333,
-0.008390822447836399,
0.024543840438127518,
0.013647614046931267,
-0.02068096399307251,
-0.011205984279513359,
-0.01443112175911665,
... | |||
wacv_2025_cf8554ac2c | cf8554ac2c | wacv | 2,025 | Shapley Consensus Deep Learning for Ensemble Pruning | This paper targets a new foundation for designing general-purpose learning systems by establishing a consensus method that facilitates self-adaptation and flexibility to deal with different learning tasks and different data distribution. We present the Shapely Consensus Deep Learning (SCDL) as a consensus method for ge... | Youcef Djenouri; Ahmed Nabil Belbachir; Asma Belhadi; Nassim Belmecheri; Tomasz Michalak | IDEAS NCBR, Warsaw, Poland + NORCE Norwegian Research Center, Oslo, Norway + University of South-Eastern Norway, Kongsberg, Norway; NORCE Norwegian Research Center, Grimstad, Norway; OsloMet University, Oslo, Norway; Simula Laboratory Research, Oslo, Norway; IDEAS NCBR, Warsaw, Poland | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Djenouri_Shapley_Consensus_Deep_Learning_for_Ensemble_Pruning_WACV_2025_paper.html | 0 | Shapley Consensus Deep Learning for Ensemble Pruning
This paper targets a new foundation for designing general-purpose learning systems by establishing a consensus method that facilitates self-adaptation and flexibility to deal with different learning tasks and different data distribution. We present the Shapely Consen... | [
-0.08170074969530106,
-0.05249033868312836,
-0.05285869166254997,
-0.02488226257264614,
-0.014282897114753723,
-0.007661747746169567,
0.051495783030986786,
-0.013242299668490887,
0.027829088270664215,
0.0017577356193214655,
-0.017367856577038765,
0.0020316983573138714,
-0.0017646423075348139... | |||
wacv_2025_1e0ed818d6 | 1e0ed818d6 | wacv | 2,025 | Shift Equivariant Pose Network | Human pose estimation has been greatly advanced in recent years. However even the best-performing models are not shift equivariant. In particular a small change in input images often results in drastic alterations in output which are problematic especially in video applications. The prevalence of top-down approaches wh... | Pengxiao Wang; Tzu-Heng Lin; Chunyu Wang; Yizhou Wang | School of Computer Science, Peking University; School of Computer Science, Peking University; Independent Researcher; School of Computer Science, Peking University + Center on Frontiers of Computing Studies, Peking University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wang_Shift_Equivariant_Pose_Network_WACV_2025_paper.html | 0 | Shift Equivariant Pose Network
Human pose estimation has been greatly advanced in recent years. However even the best-performing models are not shift equivariant. In particular a small change in input images often results in drastic alterations in output which are problematic especially in video applications. The preva... | [
-0.018321851268410683,
-0.008099058642983437,
-0.04743002727627754,
0.01882483996450901,
0.006278051529079676,
0.03057057037949562,
0.0039517260156571865,
0.03532102704048157,
0.029657738283276558,
0.03234034776687622,
-0.01009704452008009,
-0.008378497324883938,
-0.005467679817229509,
0.0... | |||
wacv_2025_ef9fbfa5a3 | ef9fbfa5a3 | wacv | 2,025 | Sifting through the Haystack - Efficiently Finding Rare Animal Behaviors in Large-Scale Datasets | In the study of animal behavior researchers often record long continuous videos accumulating into large-scale datasets. However the behaviors of interest are often rare compared to routine behaviors. This incurs a heavy cost on manual annotation forcing users to sift through many samples before finding their needles. W... | Shir Bar; Or Hirschorn; Roi Holzman; Shai Avidan | School of Zoology, the Faculty of Life Sciences, Tel Aviv University, Israel+The Interuniversity Institute for Marine Sciences in Eilat, Israel; School of Electrical Engineering, the Faculty of Engineering, Tel Aviv University, Israel; School of Zoology, the Faculty of Life Sciences, Tel Aviv University, Israel+The Int... | Poster | main | https://github.com/shir3bar/SiftingTheHaystack | https://openaccess.thecvf.com/content/WACV2025/html/Bar_Sifting_through_the_Haystack_-_Efficiently_Finding_Rare_Animal_Behaviors_WACV_2025_paper.html | 0 | Sifting through the Haystack - Efficiently Finding Rare Animal Behaviors in Large-Scale Datasets
In the study of animal behavior researchers often record long continuous videos accumulating into large-scale datasets. However the behaviors of interest are often rare compared to routine behaviors. This incurs a heavy cos... | [
-0.12147102504968643,
-0.044464390724897385,
-0.0416150726377964,
0.038953207433223724,
-0.008683865889906883,
-0.009822656400501728,
0.01293441466987133,
0.011659718118607998,
-0.030161553993821144,
0.02073255367577076,
-0.03554151952266693,
-0.01617738977074623,
-0.0033320176880806684,
0... | ||
wacv_2025_d7a13e67d6 | d7a13e67d6 | wacv | 2,025 | Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation | Multi-modal semantic segmentation significantly enhances AI agents' perception and scene understanding especially under adverse conditions like low-light or overexposed environments. Leveraging additional modalities (X-modality) like thermal and depth alongside traditional RGB provides complementary information enablin... | Zifu Wan; Pingping Zhang; Yuhao Wang; Silong Yong; Simon Stepputtis; Katia Sycara; Yaqi Xie | Robotics Institute, Carnegie Mellon University, USA; School of Future Technology, Dalian University of Technology, China; School of Future Technology, Dalian University of Technology, China; Robotics Institute, Carnegie Mellon University, USA; Robotics Institute, Carnegie Mellon University, USA; Robotics Institute, Car... | Poster | main | https://github.com/zifuwan/Sigma | https://openaccess.thecvf.com/content/WACV2025/html/Wan_Sigma_Siamese_Mamba_Network_for_Multi-Modal_Semantic_Segmentation_WACV_2025_paper.html | 53 | 2404.04256 | Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation
Multi-modal semantic segmentation significantly enhances AI agents' perception and scene understanding especially under adverse conditions like low-light or overexposed environments. Leveraging additional modalities (X-modality) like thermal and depth a... | [
-0.03847500681877136,
-0.01518701296299696,
-0.004436917137354612,
0.02875382825732231,
-0.021826092153787613,
-0.057023461908102036,
0.027170877903699875,
0.02344628982245922,
0.034303467720746994,
0.037078287452459335,
0.006243342533707619,
-0.043652184307575226,
-0.010419538244605064,
0... | |
wacv_2025_90bd43dceb | 90bd43dceb | wacv | 2,025 | Sign Language Recognition: A Large-Scale Multi-View Dataset and Comprehensive Evaluation | Vision-based sign language recognition is an extensively researched problem aimed at advancing communication between deaf and hearing individuals. Numerous Sign Language Recognition (SLR) datasets have been introduced to promote research in this field spanning multiple languages vocabulary sizes and signers. However mo... | Nguyen Son Dinh; Tuan Dung Nguyen; Duc Tri Tran; Nguyen Dang Huy Pham; Thuan Hieu Tran; Ngoc Anh Tong; Quang Huy Hoang; Phi Le Nguyen | Hanoi University of Science and Technology, Vietnam; Hanoi University of Science and Technology, Vietnam; Hanoi University of Science and Technology, Vietnam; Hanoi - Amsterdam High School for the Gifted, Vietnam; Hanoi - Amsterdam High School for the Gifted, Vietnam; Hanoi University of Science and Technology, Vietnam... | Poster | main | https://github.com/Etdihatthoc/Multi-VSL WACV 2025 | https://openaccess.thecvf.com/content/WACV2025/html/Dinh_Sign_Language_Recognition_A_Large-Scale_Multi-View_Dataset_and_Comprehensive_Evaluation_WACV_2025_paper.html | 0 | Sign Language Recognition: A Large-Scale Multi-View Dataset and Comprehensive Evaluation
Vision-based sign language recognition is an extensively researched problem aimed at advancing communication between deaf and hearing individuals. Numerous Sign Language Recognition (SLR) datasets have been introduced to promote re... | [
-0.05092298239469528,
-0.00009757827501744032,
-0.026331812143325806,
-0.032072219997644424,
-0.01672125607728958,
0.028646493330597878,
-0.025424456223845482,
0.03166483715176582,
0.012702969834208488,
-0.02314681001007557,
0.008203229866921902,
0.0031780570279806852,
0.004071523901075125,
... | ||
wacv_2025_b83c162589 | b83c162589 | wacv | 2,025 | Similarity over Factuality: Are we Making Progress on Multimodal Out-of-Context Misinformation Detection? | Out-of-context (OOC) misinformation poses a significant challenge in multimodal fact-checking where images are paired with texts that misrepresent their original context to support false narratives. Recent research in evidence-based OOC detection has seen a trend towards increasingly complex architectures incorporating... | Stefanos-Iordanis Papadopoulos; Christos Koutlis; Symeon Papadopoulos; Panagiotis C. Petrantonakis | Centre for Research & Technology Hellas, Greece+Aristotle University of Thessaloniki, Greece; Centre for Research & Technology Hellas, Greece; Centre for Research & Technology Hellas, Greece; Aristotle University of Thessaloniki, Greece | Poster | main | https://github.com/stevejpapad/outcontext-misinfo-progress | https://openaccess.thecvf.com/content/WACV2025/html/Papadopoulos_Similarity_over_Factuality_Are_we_Making_Progress_on_Multimodal_Out-of-Context_WACV_2025_paper.html | 7 | 2407.13488 | Similarity over Factuality: Are we Making Progress on Multimodal Out-of-Context Misinformation Detection?
Out-of-context (OOC) misinformation poses a significant challenge in multimodal fact-checking where images are paired with texts that misrepresent their original context to support false narratives. Recent research... | [
-0.0701751708984375,
-0.02025502175092697,
-0.04658468812704086,
0.03328010067343712,
0.00018080681911669672,
0.006978386081755161,
-0.01498163491487503,
0.057988617569208145,
0.018028274178504944,
0.018410269170999527,
-0.04949157312512398,
-0.0687217265367508,
-0.0023513620253652334,
0.0... | |
wacv_2025_37457179ad | 37457179ad | wacv | 2,025 | SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models | Computer-assisted surgical (CAS) systems enhance surgical execution and outcomes by providing advanced support to surgeons. These systems often rely on deep learning models trained on complex challenging-to-annotate data. While synthetic data generation can address these challenges enhancing the realism of such data is... | Sabina Martyniak; Joanna Kaleta; Diego Dall'Alba; Michał Naskręt; Szymon Płotka; Przemysław Korzeniowski | ;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Martyniak_SimuScope_Realistic_Endoscopic_Synthetic_Dataset_Generation_through_Surgical_Simulation_and_WACV_2025_paper.html | 1 | 2412.02332 | SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models
Computer-assisted surgical (CAS) systems enhance surgical execution and outcomes by providing advanced support to surgeons. These systems often rely on deep learning models trained on complex challenging-to-ann... | [
-0.055798664689064026,
-0.01446699257940054,
-0.035414181649684906,
0.02083827741444111,
-0.0029133653733879328,
-0.05009899660944939,
0.015447190031409264,
0.06937621533870697,
0.020529696717858315,
0.06730691343545914,
0.019585803151130676,
-0.012996695935726166,
0.006353133358061314,
0.... | ||
wacv_2025_042978796f | 042978796f | wacv | 2,025 | Single-Layer Distillation with Fourier Convolutions for Texture Anomaly Detection | In industrial quality control detecting anomalies in visual textures is essential for ensuring product quality and operational efficiency. Early identification of defects prevents faulty items from reaching consumers reduces waste and maintains high standards of production. Numerous unsupervised anomaly detection metho... | Simon Thomine; Hichem Snoussi | University of Technology of Troyes; University of Technology of Troyes | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Thomine_Single-Layer_Distillation_with_Fourier_Convolutions_for_Texture_Anomaly_Detection_WACV_2025_paper.html | 0 | Single-Layer Distillation with Fourier Convolutions for Texture Anomaly Detection
In industrial quality control detecting anomalies in visual textures is essential for ensuring product quality and operational efficiency. Early identification of defects prevents faulty items from reaching consumers reduces waste and mai... | [
-0.04365621134638786,
-0.025549013167619705,
-0.019433461129665375,
0.016698040068149567,
0.00240155216306448,
-0.005880693905055523,
-0.05371371656656265,
0.04166681319475174,
-0.003034751396626234,
0.04671398550271988,
-0.015445456840097904,
-0.018991371616721153,
-0.03433551639318466,
0... | |||
wacv_2025_bf76cb94c6 | bf76cb94c6 | wacv | 2,025 | Situational Scene Graph for Structured Human-Centric Situation Understanding | Graph based representation has been widely used in modelling spatio-temporal relationships in video understanding. Although effective existing graph-based approaches focus on capturing the human-object relationships while ignoring fine-grained semantic properties of the action components. These semantic properties are ... | Chinthani Sugandhika; Chen Li; Deepu Rajan; Basura Fernando | College of Computing and Data Science, Nanyang Technological University, Singapore + Centre for Frontier AI Research, Agency for Science, Technology and Research, Singapore + Institute of High-Performance Computing, Agency for Science, Technology and Research, Singapore; Centre for Frontier AI Research, Agency for Scie... | Poster | main | https://github.com/LUNAProject22/SSG | https://openaccess.thecvf.com/content/WACV2025/html/Sugandhika_Situational_Scene_Graph_for_Structured_Human-Centric_Situation_Understanding_WACV_2025_paper.html | 1 | 2410.22829 | Situational Scene Graph for Structured Human-Centric Situation Understanding
Graph based representation has been widely used in modelling spatio-temporal relationships in video understanding. Although effective existing graph-based approaches focus on capturing the human-object relationships while ignoring fine-grained... | [
-0.04629925638437271,
-0.018022840842604637,
-0.03697613254189491,
-0.013165885582566261,
0.008322887122631073,
-0.05221692472696304,
0.0033961471635848284,
0.017362220212817192,
0.0030635108705610037,
0.009499907493591309,
0.002419173251837492,
0.015575754456222057,
0.005564098712056875,
... | |
wacv_2025_9a31b8fdcd | 9a31b8fdcd | wacv | 2,025 | Skip-and-Play: Depth-Driven Pose-Preserved Image Generation for Any Objects | The emergence of diffusion models has enabled the generation of diverse high-quality images solely from text prompting subsequent efforts to enhance the controllability of these models. Despite the improvement in controllability pose control remains limited to specific objects (e.g. humans) or poses (e.g. frontal view)... | Kyungmin Jo; Jaegul Choo | KAIST; KAIST | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jo_Skip-and-Play_Depth-Driven_Pose-Preserved_Image_Generation_for_Any_Objects_WACV_2025_paper.html | 1 | Skip-and-Play: Depth-Driven Pose-Preserved Image Generation for Any Objects
The emergence of diffusion models has enabled the generation of diverse high-quality images solely from text prompting subsequent efforts to enhance the controllability of these models. Despite the improvement in controllability pose control re... | [
-0.04198809713125229,
-0.023449817672371864,
-0.04870914667844772,
0.015242381021380424,
-0.020938655361533165,
-0.0034805438481271267,
0.014457643032073975,
0.025905584916472435,
-0.0068226042203605175,
-0.011346387676894665,
-0.012297306209802628,
0.025019293650984764,
-0.01962768100202083... | |||
wacv_2025_e12eb94e39 | e12eb94e39 | wacv | 2,025 | Skyeyes: Ground Roaming using Aerial View Images | Integrating aerial imagery-based scene generation into applications like autonomous driving and gaming enhances realism in 3D environments but challenges remain in creating detailed content for occluded areas and ensuring real-time consistent rendering. In this paper we introduce Skyeyes a novel framework that can gene... | Zhiyuan Gao; Wenbin Teng; Gonglin Chen; Jinsen Wu; Ningli Xu; Rongjun Qin; Andrew Feng; Yajie Zhao | University of Southern California+Institute for Creative Technologies; University of Southern California+Institute for Creative Technologies; University of Southern California+Institute for Creative Technologies; University of Southern California+Institute for Creative Technologies; The Ohio State University; The Ohio ... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Gao_Skyeyes_Ground_Roaming_using_Aerial_View_Images_WACV_2025_paper.html | 2 | 2409.16685 | Skyeyes: Ground Roaming using Aerial View Images
Integrating aerial imagery-based scene generation into applications like autonomous driving and gaming enhances realism in 3D environments but challenges remain in creating detailed content for occluded areas and ensuring real-time consistent rendering. In this paper we ... | [
-0.03816966712474823,
0.0043013859540224075,
-0.019322024658322334,
-0.00832452718168497,
-0.01904834248125553,
-0.009245926514267921,
0.0011055655777454376,
0.04878856986761093,
0.006322079338133335,
0.03309740871191025,
-0.0007589003653265536,
-0.008288036100566387,
0.017990101128816605,
... | ||
wacv_2025_54b7a5333e | 54b7a5333e | wacv | 2,025 | Sli2Vol+: Segmenting 3D Medical Images Based on an Object Estimation Guided Correspondence Flow Network | Deep learning (DL) methods have shown remarkable successes in medical image segmentation often using large amounts of annotated data for model training. However acquiring a large number of diverse labeled 3D medical image datasets is highly difficult and expensive. Recently mask propagation DL methods were developed to... | Delin An; Pengfei Gu; Milan Sonka; Chaoli Wang; Danny Z. Chen | University of Notre Dame; The University of Texas Rio Grande Valley; University of Iowa; University of Notre Dame; University of Notre Dame | Poster | main | https://github.com/adlsn/Sli2Volplus | https://openaccess.thecvf.com/content/WACV2025/html/An_Sli2Vol_Segmenting_3D_Medical_Images_Based_on_an_Object_Estimation_WACV_2025_paper.html | 2 | Sli2Vol+: Segmenting 3D Medical Images Based on an Object Estimation Guided Correspondence Flow Network
Deep learning (DL) methods have shown remarkable successes in medical image segmentation often using large amounts of annotated data for model training. However acquiring a large number of diverse labeled 3D medical ... | [
-0.07684939354658127,
-0.0231916643679142,
-0.023119639605283737,
0.01656547375023365,
0.01372053474187851,
0.017303718253970146,
0.02481219917535782,
-0.03401324152946472,
-0.007206881884485483,
0.001878245733678341,
0.0062840767204761505,
0.012775221839547157,
-0.010542484000325203,
0.07... | ||
wacv_2025_10aa0019ed | 10aa0019ed | wacv | 2,025 | SmartKC++: Improving Performance of Smartphone-Based Corneal Topographers | Keratoconus an ocular condition marked by progressive corneal thinning and outward bulging presents diagnostic challenges due to the high cost and lack of portability in conventional corneal topographers. These limitations restrict accessibility for many necessitating affordable and mobile alternatives. Innovations lik... | Vaibhav Ganatra; Siddhartha Gairola; Pallavi Joshi; Anand Balasubramaniam; Kaushik Murali; Arivunithi Varadharajan; Bellamkonda Mallikarjuna; Nipun Kwatra; Mohit Jain | Microsoft Research, India; Max Planck Institute of Informatics, Saarbr ¨ucken, Germany; Sankara Eye Hospital, India; Remidio Innovative Solutions Private Limited, Bengaluru, India; Sankara Eye Hospital, India; Remidio Innovative Solutions Private Limited, Bengaluru, India; Remidio Innovative Solutions Private Limited, ... | Poster | main | https://github.com/microsoft/SmartKC-A-Smartphone-based-Corneal-Topographer | https://openaccess.thecvf.com/content/WACV2025/html/Ganatra_SmartKC_Improving_Performance_of_Smartphone-Based_Corneal_Topographers_WACV_2025_paper.html | 0 | SmartKC++: Improving Performance of Smartphone-Based Corneal Topographers
Keratoconus an ocular condition marked by progressive corneal thinning and outward bulging presents diagnostic challenges due to the high cost and lack of portability in conventional corneal topographers. These limitations restrict accessibility ... | [
-0.051368411630392075,
0.021036408841609955,
-0.016201956197619438,
-0.03507312759757042,
0.00611306494101882,
-0.021204402670264244,
0.0074570057913661,
0.016453944146633148,
0.007918985560536385,
0.03546511009335518,
0.001796587835997343,
-0.01024754997342825,
-0.01431670505553484,
0.020... | ||
wacv_2025_7c0c82380e | 7c0c82380e | wacv | 2,025 | Social EgoMesh Estimation | Accurately estimating the 3D pose of the camera wearer in egocentric video sequences is crucial to modeling human behavior in virtual and augmented reality applications. The task presents unique challenges due to the limited visibility of the user's body caused by the front-facing camera mounted on their head. Recent r... | Luca Scofano; Alessio Sampieri; Edoardo De Matteis; Indro Spinelli; Fabio Galasso | Sapienza University of Rome, Italy; Sapienza University of Rome, Italy; Sapienza University of Rome, Italy; Sapienza University of Rome, Italy; Sapienza University of Rome, Italy | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Scofano_Social_EgoMesh_Estimation_WACV_2025_paper.html | 0 | 2411.04598 | Social EgoMesh Estimation
Accurately estimating the 3D pose of the camera wearer in egocentric video sequences is crucial to modeling human behavior in virtual and augmented reality applications. The task presents unique challenges due to the limited visibility of the user's body caused by the front-facing camera mount... | [
-0.040659014135599136,
-0.021831326186656952,
-0.022930219769477844,
0.0181408803910017,
-0.015320389531552792,
0.013314911164343357,
0.015302075073122978,
0.020036470144987106,
0.0037682848051190376,
0.03642828017473221,
-0.006140060722827911,
-0.008374474942684174,
-0.0007589224842377007,
... | ||
wacv_2025_a0668d0fe8 | a0668d0fe8 | wacv | 2,025 | Socially-Informed Reconstruction for Pedestrian Trajectory Forecasting | Pedestrian trajectory prediction remains a challenge for autonomous systems particularly due to the intricate dynamics of social interactions. Accurate forecasting requires a comprehensive understanding not only of each pedestrian's previous trajectory but also of their interaction with the surrounding environment an i... | Haleh Damirchi; Ali Etemad; Michael Greenspan | Dept. ECE & Ingenuity Labs Research Institute, Queen’s University, Kingston, Canada; Dept. ECE & Ingenuity Labs Research Institute, Queen’s University, Kingston, Canada; Dept. ECE & Ingenuity Labs Research Institute, Queen’s University, Kingston, Canada | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Damirchi_Socially-Informed_Reconstruction_for_Pedestrian_Trajectory_Forecasting_WACV_2025_paper.html | 1 | 2412.04673 | Socially-Informed Reconstruction for Pedestrian Trajectory Forecasting
Pedestrian trajectory prediction remains a challenge for autonomous systems particularly due to the intricate dynamics of social interactions. Accurate forecasting requires a comprehensive understanding not only of each pedestrian's previous traject... | [
-0.050873786211013794,
-0.004010405857115984,
-0.04104546457529068,
0.028430575504899025,
-0.00946587510406971,
-0.03264809027314186,
-0.003824477316811681,
-0.009522359818220139,
0.005714357364922762,
0.04906627908349037,
-0.048501431941986084,
0.004951815586537123,
0.009122260846197605,
... | ||
wacv_2025_32c91aa43c | 32c91aa43c | wacv | 2,025 | Solar Multimodal Transformer: Intraday Solar Irradiance Predictor using Public Cameras and Time Series | Accurate intraday solar irradiance forecasting is crucial for optimizing dispatch planning and electricity trading. For this purpose we introduce a novel and effective approach that includes three distinguishing components from the literature: 1) the uncommon use of single-frame public camera imagery; 2) solar irradian... | Yanan Niu; Roy Sarkis; Demetri Psaltis; Mario Paolone; Christophe Moser; Luisa Lambertini | EPFL, Lausanne, 1015, Vaud, Switzerland; EPFL, Lausanne, 1015, Vaud, Switzerland; EPFL, Lausanne, 1015, Vaud, Switzerland; EPFL, Lausanne, 1015, Vaud, Switzerland; EPFL, Lausanne, 1015, Vaud, Switzerland; EPFL, Lausanne, 1015, Vaud, Switzerland + Universita’ della Svizzera Italiana (USI), Lugano, 6900, Ticino, Switzerl... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Niu_Solar_Multimodal_Transformer_Intraday_Solar_Irradiance_Predictor_using_Public_Cameras_WACV_2025_paper.html | 0 | Solar Multimodal Transformer: Intraday Solar Irradiance Predictor using Public Cameras and Time Series
Accurate intraday solar irradiance forecasting is crucial for optimizing dispatch planning and electricity trading. For this purpose we introduce a novel and effective approach that includes three distinguishing compo... | [
-0.06814306229352951,
0.009441949427127838,
-0.05346778407692909,
0.0037443002220243216,
-0.026331327855587006,
-0.0006450169021263719,
-0.01453804038465023,
0.027813494205474854,
0.02369636483490467,
0.027776896953582764,
-0.03196721896529198,
0.02104310318827629,
0.0206405408680439,
-0.0... | |||
wacv_2025_cd386fb2e1 | cd386fb2e1 | wacv | 2,025 | SoundLoc3D: Invisible 3D Sound Source Localization and Classification using a Multimodal RGB-D Acoustic Camera | Accurately localizing 3D sound sources and estimating their semantic labels - where the sources may not be visible but are assumed to lie on the physical surface of objects in the scene - have many real applications including detecting gas leak and machinery malfunction. The audio-visual weak- correlation in such setti... | Yuhang He; Sangyun Shin; Anoop Cherian; Niki Trigoni; Andrew Markham | Department of Computer Science, University of Oxford, UK; Department of Computer Science, University of Oxford, UK; Mitsubishi Electric Research Labs, Cambridge, MA, US; Department of Computer Science, University of Oxford, UK; Department of Computer Science, University of Oxford, UK | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/He_SoundLoc3D_Invisible_3D_Sound_Source_Localization_and_Classification_using_a_WACV_2025_paper.html | 0 | SoundLoc3D: Invisible 3D Sound Source Localization and Classification using a Multimodal RGB-D Acoustic Camera
Accurately localizing 3D sound sources and estimating their semantic labels - where the sources may not be visible but are assumed to lie on the physical surface of objects in the scene - have many real applic... | [
-0.05033703148365021,
0.009617968462407589,
-0.03338423743844032,
0.0023325819056481123,
-0.006719094701111317,
0.02475503273308277,
0.016440434381365776,
0.020817957818508148,
0.009456170722842216,
-0.007869655266404152,
-0.017878634855151176,
-0.009096620604395866,
0.03431906923651695,
-... | |||
wacv_2025_7244f8f0ac | 7244f8f0ac | wacv | 2,025 | SoundSil-DS: Deep Denoising and Segmentation of Sound-Field Images with Silhouettes | Development of optical technology has enabled imaging of two-dimensional (2D) sound fields. This acousto-optic sensing enables understanding of the interaction between sound and objects such as reflection and diffraction. Moreover it is expected to be used an advanced measurement technology for sonars in self-driving v... | Risako Tanigawa; Kenji Ishikawa; Noboru Harada; Yasuhiro Oikawa | NTT Communication Science Laboratories, NTT Corporation, Atsugi, Kanagawa 243-0198, Japan+Intermedia Art and Science, Waseda University, Shinjuku, Tokyo 169-8555, Japan; NTT Communication Science Laboratories, NTT Corporation, Atsugi, Kanagawa 243-0198, Japan; NTT Communication Science Laboratories, NTT Corporation, At... | Poster | main | https://github.com/nttcslab/soundsil-ds | https://openaccess.thecvf.com/content/WACV2025/html/Tanigawa_SoundSil-DS_Deep_Denoising_and_Segmentation_of_Sound-Field_Images_with_Silhouettes_WACV_2025_paper.html | 0 | SoundSil-DS: Deep Denoising and Segmentation of Sound-Field Images with Silhouettes
Development of optical technology has enabled imaging of two-dimensional (2D) sound fields. This acousto-optic sensing enables understanding of the interaction between sound and objects such as reflection and diffraction. Moreover it is... | [
-0.0532388873398304,
-0.005886636208742857,
-0.031358372420072556,
0.008325518108904362,
-0.013596649281680584,
0.01365218311548233,
0.012819169089198112,
0.019233381375670433,
0.006867742165923119,
0.04265034571290016,
-0.001030276995152235,
0.0048361122608184814,
0.012782146222889423,
0.... | ||
wacv_2025_df327a6b88 | df327a6b88 | wacv | 2,025 | SpaGBOL: Spatial-Graph-Based Orientated Localisation | Cross-View Geo-Localisation within urban regions is challenging in part due to the lack of geo-spatial structuring within current datasets and techniques. We propose utilising graph representations to model sequences of local observations and the connectivity of the target location. Modelling as a graph enables generat... | Tavis Shore; Oscar Mendez; Simon Hadfield | University of Surrey1; Locus Robotics2; University of Surrey1 | Poster | main | github.com/tavisshore/SpaGBOL | https://openaccess.thecvf.com/content/WACV2025/html/Shore_SpaGBOL_Spatial-Graph-Based_Orientated_Localisation_WACV_2025_paper.html | 1 | 2409.15514 | SpaGBOL: Spatial-Graph-Based Orientated Localisation
Cross-View Geo-Localisation within urban regions is challenging in part due to the lack of geo-spatial structuring within current datasets and techniques. We propose utilising graph representations to model sequences of local observations and the connectivity of the ... | [
-0.08208499848842621,
-0.020576022565364838,
-0.013939479365944862,
-0.011219135485589504,
-0.0005939340917393565,
-0.025176871567964554,
0.0393628254532814,
-0.01771874912083149,
0.008786344900727272,
0.03061755932867527,
-0.023716285824775696,
0.030106354504823685,
0.0019387013744562864,
... | |
wacv_2025_8da7ef54bb | 8da7ef54bb | wacv | 2,025 | Sparse-View 3D Reconstruction of Clothed Humans via Normal Maps | We present a novel deep learning-based approach to the 3D reconstruction of clothed humans using weak supervision via 2D normal maps. Given a single RGB image or multiview images our network is optimized to infer a person-specific signed distance function (SDF) discretized on a tetrahedral mesh surrounding the body in ... | Jane Wu; Diego Thomas; Ronald Fedkiw | Stanford University; Kyushu University; Stanford University + Epic Games | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wu_Sparse-View_3D_Reconstruction_of_Clothed_Humans_via_Normal_Maps_WACV_2025_paper.html | 0 | Sparse-View 3D Reconstruction of Clothed Humans via Normal Maps
We present a novel deep learning-based approach to the 3D reconstruction of clothed humans using weak supervision via 2D normal maps. Given a single RGB image or multiview images our network is optimized to infer a person-specific signed distance function ... | [
-0.00788346491754055,
-0.0211031436920166,
-0.051874689757823944,
0.0022346556652337313,
-0.010570164769887924,
0.013926215469837189,
0.06671196222305298,
-0.010746799409389496,
0.005550033878535032,
0.024747386574745178,
-0.03646102547645569,
0.01843503676354885,
-0.006465742830187082,
0.... | |||
wacv_2025_0a592458db | 0a592458db | wacv | 2,025 | Spatially-Adaptive Hash Encodings for Neural Surface Reconstruction | Positional encodings are a common component of neural scene reconstruction methods and provide a way to bias the learning of neural fields towards coarser or finer representations. Current neural surface reconstruction methods use a "one-size-fits-all" approach to encoding choosing a fixed set of encoding functions and... | Thomas Walker; Octave Mariotti; Amir Vaxman; Hakan Bilen | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Walker_Spatially-Adaptive_Hash_Encodings_for_Neural_Surface_Reconstruction_WACV_2025_paper.html | 0 | 2412.05179 | Spatially-Adaptive Hash Encodings for Neural Surface Reconstruction
Positional encodings are a common component of neural scene reconstruction methods and provide a way to bias the learning of neural fields towards coarser or finer representations. Current neural surface reconstruction methods use a "one-size-fits-all"... | [
-0.01584506407380104,
-0.009939778596162796,
-0.020578742027282715,
-0.012216856703162193,
-0.0008137485128827393,
-0.022355053573846817,
0.03206807002425194,
-0.000508740427903831,
0.02819420024752617,
0.014295517466962337,
-0.03941896930336952,
0.017082812264561653,
0.012292444705963135,
... | ||
wacv_2025_8d270023e1 | 8d270023e1 | wacv | 2,025 | Spatio-Temporal Context Prompting for Zero-Shot Action Detection | Spatio-temporal action detection encompasses the tasks of localizing and classifying individual actions within a video. Recent works aim to enhance this process by incorporating interaction modeling which captures the relationship between people and their surrounding context. However these approaches have primarily foc... | Wei-Jhe Huang; Min-Hung Chen; Shang-Hong Lai | ;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Huang_Spatio-Temporal_Context_Prompting_for_Zero-Shot_Action_Detection_WACV_2025_paper.html | 0 | 2408.15996 | Spatio-Temporal Context Prompting for Zero-Shot Action Detection
Spatio-temporal action detection encompasses the tasks of localizing and classifying individual actions within a video. Recent works aim to enhance this process by incorporating interaction modeling which captures the relationship between people and their... | [
-0.03569302707910538,
-0.024030771106481552,
-0.019485387951135635,
0.03685200959444046,
0.002954046241939068,
0.0002310324489371851,
0.023034770041704178,
0.014541604556143284,
-0.011571712791919708,
0.02069869637489319,
-0.0020610415376722813,
-0.022962333634495735,
-0.013391676358878613,
... | ||
wacv_2025_78caa0dee7 | 78caa0dee7 | wacv | 2,025 | SpectFormer: Frequency and Attention is What You Need in a Vision Transformer | Vision transformers have been applied successfully for image recognition tasks. There have been either multiheaded self-attention based (ViT [12] DeIT [54]) similar to the original work in textual models or more recently based on spectral layers (Fnet [29] GFNet [46] AFNO [15]). We hypothesize that spectral layers capt... | Badri N. Patro; Vinay P. Namboodiri; Vijay S. Agneeswaran | Microsoft; University of Bath; Microsoft | Poster | main | https://github.com/badripatro/SpectFormers | https://openaccess.thecvf.com/content/WACV2025/html/Patro_SpectFormer_Frequency_and_Attention_is_What_You_Need_in_a_WACV_2025_paper.html | 86 | 2304.06446 | SpectFormer: Frequency and Attention is What You Need in a Vision Transformer
Vision transformers have been applied successfully for image recognition tasks. There have been either multiheaded self-attention based (ViT [12] DeIT [54]) similar to the original work in textual models or more recently based on spectral lay... | [
-0.01067472342401743,
-0.018073316663503647,
-0.05194486305117607,
0.0024661978241056204,
-0.004213467240333557,
-0.012522096745669842,
0.022914709523320198,
0.009018458425998688,
0.011211644858121872,
0.0010761177400127053,
-0.01819162257015705,
-0.011630261316895485,
-0.011948774568736553,... | |
wacv_2025_d4ae3043a8 | d4ae3043a8 | wacv | 2,025 | SpiralMLP: A Lightweight Vision MLP Architecture | We present SpiralMLP a novel architecture introduces a Spiral FC layer as a replacement for the conventional Token Mixing approach. Differing from several existing MLP-based models that primarily emphasize axes our Spiral FC layer is designed as a deformable convolution layer with spiral-like offsets. We further adapt ... | Haojie Mu; Burhan Ul Tayyab; Nicholas Chua | Kookree; Kookree; Kookree | Poster | main | https://github.com/Kookree/SpiralMLP | https://openaccess.thecvf.com/content/WACV2025/html/Mu_SpiralMLP_A_Lightweight_Vision_MLP_Architecture_WACV_2025_paper.html | 0 | 2404.00648 | SpiralMLP: A Lightweight Vision MLP Architecture
We present SpiralMLP a novel architecture introduces a Spiral FC layer as a replacement for the conventional Token Mixing approach. Differing from several existing MLP-based models that primarily emphasize axes our Spiral FC layer is designed as a deformable convolution ... | [
-0.03372238948941231,
0.006372771691530943,
-0.015962054952979088,
0.0048757498152554035,
0.01459944061934948,
0.00482476782053709,
-0.02098611742258072,
0.000341812294209376,
0.026547808200120926,
0.012309878133237362,
-0.014775561168789864,
-0.005464361980557442,
-0.020188940688967705,
0... | |
wacv_2025_a78d851076 | a78d851076 | wacv | 2,025 | Spk2ImgMamba: Spiking Camera Image Reconstruction with Multi-Scale State Space Models | As a bio-inspired vision sensor the spiking camera has showcased remarkable capability in high-speed imaging with a sampling rate of 40000 Hz. Reconstructing clear images from continuous spike streams which is obtained by each photosensor continuously detecting photons and firing them asynchronously has garnered signif... | Jiaoyang Yin; Bin Fan; Chao Xu; Tiejun Huang; Boxin Shi | State Key Lab of Multimedia Info. Processing, School of Computer Science, Peking University + Nat’l Eng. Research Ctr. of Visual Technology, School of Computer Science, Peking University; Nat’l Key Lab of General AI, School of Intelligence Science and Technology, Peking University; Nat’l Key Lab of General AI, School o... | Poster | main | https://github.com/interstellarH/Spk2ImgMamba | https://openaccess.thecvf.com/content/WACV2025/html/Yin_Spk2ImgMamba_Spiking_Camera_Image_Reconstruction_with_Multi-Scale_State_Space_Models_WACV_2025_paper.html | 0 | Spk2ImgMamba: Spiking Camera Image Reconstruction with Multi-Scale State Space Models
As a bio-inspired vision sensor the spiking camera has showcased remarkable capability in high-speed imaging with a sampling rate of 40000 Hz. Reconstructing clear images from continuous spike streams which is obtained by each photose... | [
-0.036968398839235306,
-0.00534287141636014,
-0.03683842346072197,
-0.010648607276380062,
-0.005960249342024326,
-0.006679749581962824,
0.03384901583194733,
0.027851631864905357,
0.02844580076634884,
0.029504161328077316,
-0.02215133048593998,
0.013777273707091808,
-0.03312487527728081,
0.... | ||
wacv_2025_0eecb7928f | 0eecb7928f | wacv | 2,025 | SplatFace: Gaussian Splat Face Reconstruction Leveraging an Optimizable Surface | We present SplatFace a novel Gaussian splatting framework designed for 3D human face reconstruction without reliance on accurate pre-determined geometry. Our method is designed to simultaneously deliver both high-quality novel view rendering and accurate 3D mesh reconstructions. We incorporate a generic 3D Morphable Mo... | Jiahao Luo; Jing Liu; James Davis | University of California, Santa Cruz; ByteDance Inc.; University of California, Santa Cruz | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Luo_SplatFace_Gaussian_Splat_Face_Reconstruction_Leveraging_an_Optimizable_Surface_WACV_2025_paper.html | 4 | 2403.18784 | SplatFace: Gaussian Splat Face Reconstruction Leveraging an Optimizable Surface
We present SplatFace a novel Gaussian splatting framework designed for 3D human face reconstruction without reliance on accurate pre-determined geometry. Our method is designed to simultaneously deliver both high-quality novel view renderin... | [
-0.023526109755039215,
0.010877055115997791,
-0.016862263903021812,
-0.07216181606054306,
-0.02111317589879036,
0.044940900057554245,
0.03464822843670845,
-0.010009907186031342,
0.014157137833535671,
0.04267877712845802,
-0.02271551452577114,
0.0254112146794796,
0.02982236072421074,
0.0280... | ||
wacv_2025_9997a0cdf6 | 9997a0cdf6 | wacv | 2,025 | SpotDiffusion: A Fast Approach for Seamless Panorama Generation Over Time | Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techniques such as MultiDiffusion and SyncDiffusion have further pushed image generation beyond training resolutions i.e. from square images to pa... | Stanislav Frolov; Brian B. Moser; Andreas Dengel | German Research Center for Artificial Intelligence (DFKI), Germany; RPTU Kaiserslautern-Landau, Germany; German Research Center for Artificial Intelligence (DFKI), Germany | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Frolov_SpotDiffusion_A_Fast_Approach_for_Seamless_Panorama_Generation_Over_Time_WACV_2025_paper.html | 5 | 2407.15507 | SpotDiffusion: A Fast Approach for Seamless Panorama Generation Over Time
Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techniques such as MultiDiffusion and SyncDiffusion have further pushed ... | [
-0.06536485999822617,
-0.010165650397539139,
-0.03079620935022831,
0.031993232667446136,
-0.007073333952575922,
-0.026388976722955704,
-0.02450275421142578,
0.03979203850030899,
0.02881930209696293,
0.016576992347836494,
-0.023432686924934387,
-0.0060168681666255,
-0.01322169415652752,
0.0... | ||
wacv_2025_22f4e76c8a | 22f4e76c8a | wacv | 2,025 | Stable Autofocus with Focal Consistency Loss | Autofocus aims to accurately position the camera lens to bring the desired region of interest into focus. Conventional works search for the sharpest frame within the lens movement. However sharpness measure in many real-world settings is ambiguous and may cause a focus hunting problem where the lens continuously moves ... | Sangwon Lee; Myungsub Choi; Nagyeong Lee; Hyong-Euk Lee | Samsung Advanced Institute of Technology (SAIT)+*; Samsung Advanced Institute of Technology (SAIT); Samsung Advanced Institute of Technology (SAIT); Samsung Advanced Institute of Technology (SAIT) | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lee_Stable_Autofocus_with_Focal_Consistency_Loss_WACV_2025_paper.html | 0 | Stable Autofocus with Focal Consistency Loss
Autofocus aims to accurately position the camera lens to bring the desired region of interest into focus. Conventional works search for the sharpest frame within the lens movement. However sharpness measure in many real-world settings is ambiguous and may cause a focus hunti... | [
-0.06467696279287338,
-0.04305648431181908,
-0.051431652158498764,
-0.017229972407221794,
-0.005953933112323284,
-0.002522696740925312,
0.023428335785865784,
-0.002331303898245096,
-0.0018343741539865732,
0.009804850444197655,
-0.041765160858631134,
-0.016704218462109566,
-0.0059769926592707... | |||
wacv_2025_68bf8f18ee | 68bf8f18ee | wacv | 2,025 | Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning | Few-shot class incremental learning implies the model to learn new classes while retaining knowledge of previously learned classes with a small number of training instances. Existing frameworks typically freeze the parameters of the previously learned classes during the incorporation of new classes. However this approa... | Parinita Nema; Vinod K Kurmi | Indian Institute of Science Education and Research Bhopal, India; Indian Institute of Science Education and Research Bhopal, India | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Nema_Strategic_Base_Representation_Learning_via_Feature_Augmentations_for_Few-Shot_Class_WACV_2025_paper.html | 0 | 2501.09361 | Strategic Base Representation Learning via Feature Augmentations for Few-Shot Class Incremental Learning
Few-shot class incremental learning implies the model to learn new classes while retaining knowledge of previously learned classes with a small number of training instances. Existing frameworks typically freeze the ... | [
-0.07678106427192688,
-0.052975259721279144,
-0.011535528115928173,
0.01014869287610054,
0.0010297938715666533,
-0.02792038582265377,
0.021693404763936996,
0.043423548340797424,
-0.013638741336762905,
0.013693847693502903,
-0.061608538031578064,
-0.02397112175822258,
-0.0634821429848671,
0... | ||
wacv_2025_035a54d68b | 035a54d68b | wacv | 2,025 | Stratified Domain Adaptation: A Progressive Self-Training Approach for Scene Text Recognition | Unsupervised domain adaptation (UDA) has become increasingly prevalent in scene text recognition (STR) especially where training and testing data reside in different domains. The efficacy of existing UDA approaches tends to degrade when there is a large gap between the source and target domains. To deal with this probl... | Kha Nhat Le; Hoang-Tuan Nguyen; Hung Tien Tran; Thanh Duc Ngo | University of Information Technology, VNU-HCM, Vietnam; University of Information Technology, VNU-HCM, Vietnam; University of Information Technology, VNU-HCM, Vietnam; Vietnam National University, Ho Chi Minh City, Vietnam | Poster | main | https://github.com/KhaLee2307/StrDA | https://openaccess.thecvf.com/content/WACV2025/html/Le_Stratified_Domain_Adaptation_A_Progressive_Self-Training_Approach_for_Scene_Text_WACV_2025_paper.html | 0 | 2410.09913 | Stratified Domain Adaptation: A Progressive Self-Training Approach for Scene Text Recognition
Unsupervised domain adaptation (UDA) has become increasingly prevalent in scene text recognition (STR) especially where training and testing data reside in different domains. The efficacy of existing UDA approaches tends to de... | [
-0.06670917570590973,
-0.016242705285549164,
-0.02902681939303875,
-0.01647810824215412,
-0.0027727584820240736,
-0.012231825850903988,
-0.006134020630270243,
0.011380759067833424,
0.046790581196546555,
0.024807700887322426,
-0.014450032263994217,
-0.023087458685040474,
-0.02428257279098034,... | |
wacv_2025_582ba68d70 | 582ba68d70 | wacv | 2,025 | Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Person Images | Most virtual try-on research is motivated to serve the fashion business by generating images to demonstrate garments on studio models at a lower cost. However virtual try-on should be a broader application that also allows customers to visualize garments on themselves using their own casual photos known as in-the-wild ... | Aiyu Cui; Jay Mahajan; Viraj Shah; Preeti Gomathinayagam; Chang Liu; Svetlana Lazebnik | University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Cui_Street_TryOn_Learning_In-the-Wild_Virtual_Try-On_from_Unpaired_Person_Images_WACV_2025_paper.html | 17 | 2311.16094 | Street TryOn: Learning In-the-Wild Virtual Try-On from Unpaired Person Images
Most virtual try-on research is motivated to serve the fashion business by generating images to demonstrate garments on studio models at a lower cost. However virtual try-on should be a broader application that also allows customers to visual... | [
-0.05900442600250244,
0.008365876972675323,
-0.03863205388188362,
0.016250738874077797,
0.0011023245751857758,
0.045649204403162,
0.02027805522084236,
0.0450078509747982,
0.013836235739290714,
0.03614209592342377,
-0.028709953650832176,
0.00891291256994009,
-0.007300099823623896,
0.0006519... | ||
wacv_2025_5bb17936fd | 5bb17936fd | wacv | 2,025 | Structure-Aware Human Body Reshaping with Adaptive Affinity-Graph Network | Given a source portrait the automatic human body reshaping task aims at editing it to an aesthetic body shape. As the technology has been widely used in media several methods have been proposed mainly focusing on generating optical flow to warp the body shape. However those previous works only consider the local transf... | Qiwen Deng; Yangcen Liu | University of Electronic Science and Technology of China; Georgia Institute of Technology | Poster | main | https://github.com/Randle-Github/AGGN | https://openaccess.thecvf.com/content/WACV2025/html/Deng_Structure-Aware_Human_Body_Reshaping_with_Adaptive_Affinity-Graph_Network_WACV_2025_paper.html | 0 | 2404.13983 | Structure-Aware Human Body Reshaping with Adaptive Affinity-Graph Network
Given a source portrait the automatic human body reshaping task aims at editing it to an aesthetic body shape. As the technology has been widely used in media several methods have been proposed mainly focusing on generating optical flow to warp t... | [
-0.046503014862537384,
-0.029105806723237038,
-0.04002278298139572,
-0.00808648020029068,
-0.010916978120803833,
-0.05935301631689072,
0.0046875812113285065,
-0.03420530632138252,
0.017636535689234734,
0.017581306397914886,
-0.037997711449861526,
0.00047721510054543614,
-0.016835711896419525... | |
wacv_2025_d1e014bd26 | d1e014bd26 | wacv | 2,025 | Structured Human Assessment of Text-to-Image Generative Models | Following the great progress in text-conditioned image generation there is a dire need for establishing clear comparison benchmarks. Unfortunately assessing performance of such models is highly subjective and notoriously difficult. Current automatic assessment of generated images quality and their alignment to text are... | Ciprian A. Corneanu; Qianli Feng; Aleix M. Martinez | Amazon; Amazon; Amazon | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Corneanu_Structured_Human_Assessment_of_Text-to-Image_Generative_Models_WACV_2025_paper.html | 0 | Structured Human Assessment of Text-to-Image Generative Models
Following the great progress in text-conditioned image generation there is a dire need for establishing clear comparison benchmarks. Unfortunately assessing performance of such models is highly subjective and notoriously difficult. Current automatic assessm... | [
-0.040841925889253616,
-0.013738235458731651,
-0.01286538876593113,
-0.014147381298244,
0.015574849210679531,
-0.07557392865419388,
0.02316679246723652,
0.013710958883166313,
-0.01428376417607069,
0.01623857580125332,
-0.026367228478193283,
-0.021439284086227417,
-0.048952121287584305,
0.0... | |||
wacv_2025_52fe3d17b9 | 52fe3d17b9 | wacv | 2,025 | Style-Pro: Style-Guided Prompt Learning for Generalizable Vision-Language Models | Pre-trained Vision-language (VL) models such as CLIP have shown significant generalization ability to downstream tasks even with minimal fine-tuning. While prompt learning has emerged as an effective strategy to adapt pre-trained VL models for downstream tasks current approaches frequently encounter severe overfitting ... | Niloufar Alipour Talemi; Hossein Kashiani; Fatemeh Afghah | Clemson University; Clemson University; Clemson University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Talemi_Style-Pro_Style-Guided_Prompt_Learning_for_Generalizable_Vision-Language_Models_WACV_2025_paper.html | 0 | Style-Pro: Style-Guided Prompt Learning for Generalizable Vision-Language Models
Pre-trained Vision-language (VL) models such as CLIP have shown significant generalization ability to downstream tasks even with minimal fine-tuning. While prompt learning has emerged as an effective strategy to adapt pre-trained VL models... | [
-0.07413720339536667,
-0.04604502022266388,
-0.020351389423012733,
-0.00832680705934763,
0.004345112480223179,
-0.001980626257136464,
-0.029364148154854774,
0.02591167949140072,
-0.007636313792318106,
-0.005973678082227707,
0.00852214451879263,
-0.018061857670545578,
0.003073150757700205,
... | |||
wacv_2025_8703b1ca80 | 8703b1ca80 | wacv | 2,025 | Sun Off Lights On: Photorealistic Monocular Nighttime Simulation for Robust Semantic Perception | Nighttime scenes are hard to semantically perceive with learned models and annotate for humans. Thus realistic synthetic nighttime data become all the more important for learning robust semantic perception at night thanks to their accurate and cheap semantic annotations. However existing data-driven or hand-crafted tec... | Konstantinos Tzevelekakis; Shutong Zhang; Luc Van Gool; Christos Sakaridis | ETH Zürich; University of Toronto; ETH Zürich+KU Leuven+INSAIT; ETH Zürich | Poster | main | https://github.com/ktzevel/SOLO | https://openaccess.thecvf.com/content/WACV2025/html/Tzevelekakis_Sun_Off_Lights_On_Photorealistic_Monocular_Nighttime_Simulation_for_Robust_WACV_2025_paper.html | 0 | 2407.20336 | Sun Off Lights On: Photorealistic Monocular Nighttime Simulation for Robust Semantic Perception
Nighttime scenes are hard to semantically perceive with learned models and annotate for humans. Thus realistic synthetic nighttime data become all the more important for learning robust semantic perception at night thanks to... | [
-0.03847381845116615,
0.005870222579687834,
-0.00896517839282751,
-0.017689431086182594,
-0.01611415483057499,
-0.007135077379643917,
0.0227951817214489,
0.07324110716581345,
-0.010100304149091244,
-0.0027799000963568687,
-0.01875505968928337,
-0.016846194863319397,
-0.0028540308121591806,
... | |
wacv_2025_f20a4e9082 | f20a4e9082 | wacv | 2,025 | Survival Prediction in Lung Cancer through Multi-Modal Representation Learning | Survival prediction is a crucial task associated with cancer diagnosis and treatment planning. This paper presents a novel approach to survival prediction by harnessing comprehensive information from CT and PET scans along with associated Genomic data. Current methods rely on either a single modality or the integration... | Aiman Farooq; Deepak Mishra; Santanu Chaudhury | Indian Institute of Technology Jodhpur; Indian Institute of Technology Jodhpur; Indian Institute of Technology Delhi | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Farooq_Survival_Prediction_in_Lung_Cancer_through_Multi-Modal_Representation_Learning_WACV_2025_paper.html | 3 | 2409.20179 | Survival Prediction in Lung Cancer through Multi-Modal Representation Learning
Survival prediction is a crucial task associated with cancer diagnosis and treatment planning. This paper presents a novel approach to survival prediction by harnessing comprehensive information from CT and PET scans along with associated Ge... | [
-0.04483319818973541,
-0.023956097662448883,
-0.036816541105508804,
-0.002642492763698101,
-0.010476099327206612,
-0.05981514975428581,
0.013282868079841137,
-0.01018509641289711,
0.027842393144965172,
0.016849998384714127,
-0.014521976932883263,
0.02384345233440399,
0.008547033183276653,
... | ||
wacv_2025_041a622e28 | 041a622e28 | wacv | 2,025 | Swap Path Network for Robust Person Search Pre-Training | In person search we detect and rank matches to a query person image within a set of gallery scenes. Most person search models make use of a feature extraction backbone followed by separate heads for detection and re-identification. While pre-training methods for vision backbones are well-established pre-training additi... | Lucas Jaffe; Avideh Zakhor | Lawrence Livermore National Laboratory + University of California, Berkeley; University of California, Berkeley | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jaffe_Swap_Path_Network_for_Robust_Person_Search_Pre-Training_WACV_2025_paper.html | 0 | 2412.05433 | Swap Path Network for Robust Person Search Pre-Training
In person search we detect and rank matches to a query person image within a set of gallery scenes. Most person search models make use of a feature extraction backbone followed by separate heads for detection and re-identification. While pre-training methods for v... | [
-0.02652723714709282,
-0.04792376980185509,
-0.06469151377677917,
0.010493781417608261,
-0.012956892140209675,
-0.02232600748538971,
0.051158346235752106,
-0.007166258059442043,
0.018412914127111435,
-0.004545136354863644,
0.002725687576457858,
-0.005618680734187365,
-0.024705465883016586,
... | ||
wacv_2025_7f20f970ad | 7f20f970ad | wacv | 2,025 | Swin-: Gradient-Based Image Restoration from Image Sequences using Video Swin-Transformers | Most deep-learning models for vision tasks rely on RGB images as their primary input layer assuming the model inherently discovers an optimal representation. In this work we challenge this assumption and show that image gradients offer a straightforward yet robust representation for multi-frame image restoration. We de... | Monika Kwiatkowski; Simon Matern; Olaf Hellwich | Technische Universit ¨at Berlin, Germany; Technische Universit ¨at Berlin, Germany; Technische Universit ¨at Berlin, Germany | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kwiatkowski_Swin-_Gradient-Based_Image_Restoration_from_Image_Sequences_using_Video_Swin-Transformers_WACV_2025_paper.html | 0 | Swin-: Gradient-Based Image Restoration from Image Sequences using Video Swin-Transformers
Most deep-learning models for vision tasks rely on RGB images as their primary input layer assuming the model inherently discovers an optimal representation. In this work we challenge this assumption and show that image gradients... | [
-0.03670483082532883,
-0.02847757376730442,
-0.0301121287047863,
0.006965018808841705,
-0.0068923719227313995,
0.018089070916175842,
0.004785612691193819,
0.010016187094151974,
0.01829793117940426,
0.014365918934345245,
-0.02233891375362873,
0.00935328472405672,
-0.04475047439336777,
0.040... | |||
wacv_2025_2dc4172671 | 2dc4172671 | wacv | 2,025 | SwinIA: Self-Supervised Blind-Spot Image Denoising without Convolutions | Self-supervised image denoising implies restoring the signal from a noisy image without access to the ground truth. State-of-the-art solutions for this task rely on predicting masked pixels with a fully-convolutional neural network. This most often requires multiple forward passes information about the noise model or i... | Mikhail Papkov; Pavel Chizhov; Leopold Parts | Institute of Computer Science, University of Tartu, Estonia; Institute of Computer Science, University of Tartu, Estonia + CAIRO, Technical University of Applied Sciences Würzburg-Schweinfurt, Germany; Institute of Computer Science, University of Tartu, Estonia | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Papkov_SwinIA_Self-Supervised_Blind-Spot_Image_Denoising_without_Convolutions_WACV_2025_paper.html | 0 | 2305.05651 | SwinIA: Self-Supervised Blind-Spot Image Denoising without Convolutions
Self-supervised image denoising implies restoring the signal from a noisy image without access to the ground truth. State-of-the-art solutions for this task rely on predicting masked pixels with a fully-convolutional neural network. This most often... | [
-0.03193967416882515,
0.0020908431615680456,
-0.019754379987716675,
0.021922316402196884,
-0.01473635621368885,
-0.011185427196323872,
-0.0006710555171594024,
0.03283675014972687,
0.032818060368299484,
0.036462437361478806,
-0.016810845583677292,
-0.002586104441434145,
-0.006802832707762718,... | ||
wacv_2025_14d9ad4f8d | 14d9ad4f8d | wacv | 2,025 | SynDRA: Synthetic Dataset for Railway Applications | The use of deep learning techniques in railway environments faces significant obstacles especially for computer vision tasks. Such obstacles are mainly due to the inherent safety concerns required for installing the proper equipment on a train and the substantial effort required to precisely annotate large datasets esp... | Gianluca D'Amico; Federico Nesti; Giulio Rossolini; Mauro Marinoni; Salvatore Sabina; Giorgio Buttazzo | Scuola Superiore Sant’Anna, Italy; Scuola Superiore Sant’Anna, Italy; Scuola Superiore Sant’Anna, Italy; Scuola Superiore Sant’Anna, Italy; Scuola Superiore Sant’Anna, Italy; Scuola Superiore Sant’Anna, Italy | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/DAmico_SynDRA_Synthetic_Dataset_for_Railway_Applications_WACV_2025_paper.html | 0 | SynDRA: Synthetic Dataset for Railway Applications
The use of deep learning techniques in railway environments faces significant obstacles especially for computer vision tasks. Such obstacles are mainly due to the inherent safety concerns required for installing the proper equipment on a train and the substantial effor... | [
-0.0012676562182605267,
-0.026186589151620865,
-0.01970512792468071,
0.0232438575476408,
-0.019928626716136932,
-0.003545712446793914,
0.01976100355386734,
0.05691764876246452,
0.02665221132338047,
-0.003880960401147604,
-0.002214033156633377,
-0.008176324889063835,
0.007366142235696316,
0... | |||
wacv_2025_160ea2fc8c | 160ea2fc8c | wacv | 2,025 | SynDroneVision: A Synthetic Dataset for Image-Based Drone Detection | Developing robust drone detection systems is often constrained by the limited availability of large-scale annotated training data and the high costs associated with real-world data collection. However leveraging synthetic data generated via game engine-based simulations provides a promising and cost-effective solution ... | Tamara R. Lenhard; Andreas Weinmann; Kai Franke; Tobias Koch | Institute for the Protection of Terrestrial Infrastructures, German Aerospace Center (DLR), Germany+Working Group Algorithms for Computer Vision, Imaging and Data Analysis, University of Applied Sciences Darmstadt, Germany; Working Group Algorithms for Computer Vision, Imaging and Data Analysis, University of Applied S... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lenhard_SynDroneVision_A_Synthetic_Dataset_for_Image-Based_Drone_Detection_WACV_2025_paper.html | 4 | 2411.05633 | SynDroneVision: A Synthetic Dataset for Image-Based Drone Detection
Developing robust drone detection systems is often constrained by the limited availability of large-scale annotated training data and the high costs associated with real-world data collection. However leveraging synthetic data generated via game engine... | [
-0.03614509105682373,
-0.009960021823644638,
0.0007631214684806764,
-0.009324372746050358,
-0.024328427389264107,
-0.018118275329470634,
0.014770830981433392,
0.06233930587768555,
0.03202937915921211,
0.024163799360394478,
-0.013188567943871021,
-0.01775243505835533,
-0.01988345943391323,
... | ||
wacv_2025_798eb5d3f1 | 798eb5d3f1 | wacv | 2,025 | SyncDiff: Diffusion-Based Talking Head Synthesis with Bottlenecked Temporal Visual Prior for Improved Synchronization | Talking head synthesis also known as speech-to-lip synthesis reconstructs the facial motions that align with the given audio tracks. The synthesized videos are evaluated on mainly two aspects lip-speech synchronization and image fidelity. Recent studies demonstrate that GAN-based and diffusion-based models achieve stat... | Xulin Fan; Heting Gao; Ziyi Chen; Peng Chang; Mei Han; Mark Hasegawa-Johnson | University of Illinois at Urbana-Champaign; University of Illinois at Urbana-Champaign; PAII Inc.; PAII Inc.; PAII Inc.; University of Illinois at Urbana-Champaign | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Fan_SyncDiff_Diffusion-Based_Talking_Head_Synthesis_with_Bottlenecked_Temporal_Visual_Prior_WACV_2025_paper.html | 0 | SyncDiff: Diffusion-Based Talking Head Synthesis with Bottlenecked Temporal Visual Prior for Improved Synchronization
Talking head synthesis also known as speech-to-lip synthesis reconstructs the facial motions that align with the given audio tracks. The synthesized videos are evaluated on mainly two aspects lip-speech... | [
-0.047249164432287216,
-0.008531604893505573,
0.0011705361539497972,
-0.007521462626755238,
-0.013896278105676174,
-0.00024215537996497005,
-0.0358554907143116,
0.01636248081922531,
0.003742530709132552,
0.028866400942206383,
-0.009964914061129093,
-0.02411600388586521,
-0.04240776225924492,... | |||
wacv_2025_cf2d043abf | cf2d043abf | wacv | 2,025 | SyncViolinist: Music-Oriented Violin Motion Generation Based on Bowing and Fingering | Automatically generating realistic musical performance motion can greatly enhance digital media production often involving collaboration between professionals and musicians. However capturing the intricate body hand and finger movements required for accurate musical performances is challenging. Existing methods often f... | Hiroki Nishizawa; Keitaro Tanaka; Asuka Hirata; Shugo Yamaguchi; Qi Feng; Masatoshi Hamanaka; Shigeo Morishima | Waseda University; Waseda University; Waseda University; Waseda University; Waseda Research Institute for Science and Engineering+RIKEN; RIKEN; Waseda Research Institute for Science and Engineering | Poster | main | https://github.com/Kakanat/SyncViolinist | https://openaccess.thecvf.com/content/WACV2025/html/Nishizawa_SyncViolinist_Music-Oriented_Violin_Motion_Generation_Based_on_Bowing_and_Fingering_WACV_2025_paper.html | 0 | 2412.08343 | SyncViolinist: Music-Oriented Violin Motion Generation Based on Bowing and Fingering
Automatically generating realistic musical performance motion can greatly enhance digital media production often involving collaboration between professionals and musicians. However capturing the intricate body hand and finger movement... | [
-0.046936385333538055,
0.009732932783663273,
-0.05894336476922035,
0.060689836740493774,
0.0004980168887414038,
-0.03984135016798973,
-0.0322733111679554,
0.039186421781778336,
-0.008636840619146824,
0.042788516730070114,
0.02223110944032669,
0.013034852221608162,
0.006954043637961149,
0.0... | |
wacv_2025_cf6d714771 | cf6d714771 | wacv | 2,025 | TACLE: Task and Class-Aware Exemplar-Free Semi-Supervised Class Incremental Learning | We propose a novel TACLE (TAsk and CLass-awarE) framework for the relatively unexplored and challenging problem of exemplar-free semi-supervised class incremental learning. In this scenario at each new task the model has to learn new classes from both (few) labeled and unlabeled data without access to exemplars from pr... | Jayateja Kalla; Rohit Kumar; Soma Biswas | Department of Electrical Engineering, Indian Institute of Science, Bangalore, India; Department of Electrical Engineering, Indian Institute of Science, Bangalore, India; Department of Electrical Engineering, Indian Institute of Science, Bangalore, India | Poster | main | https://github.com/rokmr/TACLE | https://openaccess.thecvf.com/content/WACV2025/html/Kalla_TACLE_Task_and_Class-Aware_Exemplar-Free_Semi-Supervised_Class_Incremental_Learning_WACV_2025_paper.html | 0 | 2407.08041 | TACLE: Task and Class-Aware Exemplar-Free Semi-Supervised Class Incremental Learning
We propose a novel TACLE (TAsk and CLass-awarE) framework for the relatively unexplored and challenging problem of exemplar-free semi-supervised class incremental learning. In this scenario at each new task the model has to learn new c... | [
-0.056483831256628036,
-0.013545151799917221,
-0.00480752345174551,
0.02184407040476799,
-0.0043025510385632515,
0.009761284105479717,
0.07183866202831268,
0.03374406322836876,
-0.023635467514395714,
0.02440320886671543,
-0.0016497300239279866,
-0.038094598799943924,
-0.03518814966082573,
... | |
wacv_2025_76eeb3627c | 76eeb3627c | wacv | 2,025 | TAM-VT: Transformation-Aware Multi-Scale Video Transformer for Segmentation and Tracking | Video Object Segmentation (VOS) has emerged as an increasingly important problem with availability of larger datasets and more complex and realistic settings which involve long videos with global motion (e.g. in egocentric settings) depicting small objects undergoing both rigid and non-rigid (including state) deformati... | Raghav Goyal; Wan-Cyuan Fan; Mennatullah Siam; Leonid Sigal | UBC; UBC; UBC; UBC+Vector Institute for AI+CIFAR AI Chair | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Goyal_TAM-VT_Transformation-Aware_Multi-Scale_Video_Transformer_for_Segmentation_and_Tracking_WACV_2025_paper.html | 0 | TAM-VT: Transformation-Aware Multi-Scale Video Transformer for Segmentation and Tracking
Video Object Segmentation (VOS) has emerged as an increasingly important problem with availability of larger datasets and more complex and realistic settings which involve long videos with global motion (e.g. in egocentric settings... | [
-0.014924143441021442,
-0.0387471579015255,
-0.04089771583676338,
0.05828758701682091,
-0.024064023047685623,
0.03437187895178795,
-0.017779197543859482,
0.02061571180820465,
0.005186371970921755,
0.03594772145152092,
0.015359818004071712,
-0.029792670160531998,
0.02986682765185833,
0.0190... | |||
wacv_2025_20478599d6 | 20478599d6 | wacv | 2,025 | TFM^2: Training-Free Mask Matching for Open-Vocabulary Semantic Segmentation | The potential of Open-Vocabulary Semantic Segmentation (OVSS) in few-shot scenarios is not fully explored due to the complexity of extending few-shot concepts to semantic segmentation tasks. To address this challenge we propose Training-Free Mask Matching (TFM^2) an efficient mask-based adapter method that enhances OVS... | Yaoxin Zhuo; Zachary Bessinger; Lichen Wang; Naji Khosravan; Baoxin Li; Sing Bing Kang | Arizona State University; Zillow Group; Zillow Group; Zillow Group; Arizona State University; Zillow Group | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhuo_TFM2_Training-Free_Mask_Matching_for_Open-Vocabulary_Semantic_Segmentation_WACV_2025_paper.html | 0 | TFM^2: Training-Free Mask Matching for Open-Vocabulary Semantic Segmentation
The potential of Open-Vocabulary Semantic Segmentation (OVSS) in few-shot scenarios is not fully explored due to the complexity of extending few-shot concepts to semantic segmentation tasks. To address this challenge we propose Training-Free M... | [
-0.0009502823231741786,
-0.00221125571988523,
-0.043373845517635345,
0.01890094392001629,
0.013629438355565071,
-0.029717091470956802,
0.012764510698616505,
0.02013915590941906,
0.02223319187760353,
0.03186575323343277,
-0.043264590203762054,
-0.015586906112730503,
0.01078883372247219,
0.0... | |||
wacv_2025_482fd4129c | 482fd4129c | wacv | 2,025 | TLDR: Text Based Last-Layer Retraining for Debiasing Image Classifiers | An image classifier may depend on incidental features stemming from a strong correlation between the feature and the classification target in the training dataset. Recently Last Layer Retraining (LLR) with group-balanced datasets is shown to be efficient in mitigating the spurious correlation of classifiers. However th... | Juhyeon Park; Seokhyeon Jeong; Taesup Moon | IPAI, Seoul National University; ECE, Seoul National University; ASRI / INMC / AIIS, Seoul National University | Poster | main | https://github.com/beotborry/TLDR | https://openaccess.thecvf.com/content/WACV2025/html/Park_TLDR_Text_Based_Last-Layer_Retraining_for_Debiasing_Image_Classifiers_WACV_2025_paper.html | 0 | 2311.18291 | TLDR: Text Based Last-Layer Retraining for Debiasing Image Classifiers
An image classifier may depend on incidental features stemming from a strong correlation between the feature and the classification target in the training dataset. Recently Last Layer Retraining (LLR) with group-balanced datasets is shown to be effi... | [
-0.04171478748321533,
-0.01789219304919243,
-0.006866782903671265,
0.0023111130576580763,
-0.012631943449378014,
0.002462586387991905,
-0.00033220817567780614,
-0.03247951716184616,
-0.017965633422136307,
-0.016983354464173317,
-0.029450053349137306,
-0.0377122238278389,
-0.03093724511563778... | |
wacv_2025_1281ef1eb4 | 1281ef1eb4 | wacv | 2,025 | TORE: Token Recycling in Vision Transformers for Efficient Active Visual Exploration | Active Visual Exploration (AVE) optimizes the utilization of robotic resources in real-world scenarios by sequentially selecting the most informative observations. However modern methods require a high computational budget due to processing the same observations multiple times through the autoencoder transformers. As a... | Jan Olszewski; Dawid Damian Rymarczyk; Piotr Wojcik; Mateusz Pach; Bartosz Zielinski | University of Warsaw; Faculty of Mathematics and Computer Science, Jagiellonian University + Ardigen SA; Center for Molecular Medicine Cologne (CMMC), University of Cologne; Faculty of Mathematics and Computer Science, Jagiellonian University; IDEAS NCBR | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Olszewski_TORE_Token_Recycling_in_Vision_Transformers_for_Efficient_Active_Visual_WACV_2025_paper.html | 0 | 2311.15335 | TORE: Token Recycling in Vision Transformers for Efficient Active Visual Exploration
Active Visual Exploration (AVE) optimizes the utilization of robotic resources in real-world scenarios by sequentially selecting the most informative observations. However modern methods require a high computational budget due to proce... | [
0.022528504952788353,
-0.033615145832300186,
0.0008833791362121701,
0.06177110597491264,
0.0019478744361549616,
-0.0034166674595326185,
-0.00033740175422281027,
0.029296405613422394,
0.03490516170859337,
0.02574419230222702,
-0.008824443444609642,
-0.022397633641958237,
-0.006239741574972868... | ||
wacv_2025_7ab5b860f0 | 7ab5b860f0 | wacv | 2,025 | TPD-STR: Text Polygon Detection with Split Transformers | Regressing text in natural scenes with polygonal representations is challenging due to shape prediction difficulties. To address this we introduce Text Polygon Detection with Split Transformers (TPD-STR) which directly regresses polygonal points. TPD-STR incorporates the Decoder Split (DS) architecture to separate poly... | Sangyeon Kim; Sangkuk Lee; Jeesoo Kim; Nojun Kwak | NAVER WEBTOON AI; NAVER WEBTOON AI + Seoul National University; NAVER WEBTOON AI; Seoul National University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kim_TPD-STR_Text_Polygon_Detection_with_Split_Transformers_WACV_2025_paper.html | 0 | TPD-STR: Text Polygon Detection with Split Transformers
Regressing text in natural scenes with polygonal representations is challenging due to shape prediction difficulties. To address this we introduce Text Polygon Detection with Split Transformers (TPD-STR) which directly regresses polygonal points. TPD-STR incorpora... | [
-0.06243792176246643,
-0.042020536959171295,
-0.010662618093192577,
0.027068784460425377,
0.003640668001025915,
-0.005206248257309198,
0.014896168373525143,
-0.017499292269349098,
0.0658099427819252,
0.04639304429292679,
-0.0468377061188221,
0.009361056610941887,
-0.01547052338719368,
0.02... | |||
wacv_2025_0cebaa9557 | 0cebaa9557 | wacv | 2,025 | TPP-Gaze: Modelling Gaze Dynamics in Space and Time with Neural Temporal Point Processes | Attention guides our gaze to fixate the proper location of the scene and holds it in that location for the deserved amount of time given current processing demands before shifting to the next one. As such gaze deployment crucially is a temporal process. Existing computational models have made significant strides in pre... | Alessandro D'Amelio; Giuseppe Cartella; Vittorio Cuculo; Manuele Lucchi; Marcella Cornia; Rita Cucchiara; Giuseppe Boccignone | University of Milan, Italy; University of Modena and Reggio Emilia, Italy; University of Modena and Reggio Emilia, Italy; University of Milan, Italy; University of Modena and Reggio Emilia, Italy; University of Modena and Reggio Emilia, Italy; University of Milan, Italy | Poster | main | https://github.com/phuselab/tppgaze | https://openaccess.thecvf.com/content/WACV2025/html/DAmelio_TPP-Gaze_Modelling_Gaze_Dynamics_in_Space_and_Time_with_Neural_WACV_2025_paper.html | 3 | TPP-Gaze: Modelling Gaze Dynamics in Space and Time with Neural Temporal Point Processes
Attention guides our gaze to fixate the proper location of the scene and holds it in that location for the deserved amount of time given current processing demands before shifting to the next one. As such gaze deployment crucially ... | [
-0.019777992740273476,
-0.04186310991644859,
-0.001454742974601686,
0.013200833462178707,
0.00014543069119099528,
-0.028169220313429832,
0.017266206443309784,
0.0034653351176530123,
0.02256886661052704,
0.04882168769836426,
-0.019852416589856148,
-0.015582378953695297,
-0.029136722907423973,... | ||
wacv_2025_e2d8f3248d | e2d8f3248d | wacv | 2,025 | TRH2TQA: Table Recognition with Hierarchical Relationships to Table Question-Answering on Business Table Images | Despite advancements in visual question answering challenges persist with documents like financial reports often structured in complicated tabular structures with complex numerical computations. An alternative approach the pipeline-driven methodology includes table recognition (TR) and table question-answering (TQA). R... | Pongsakorn Jirachanchaisiri; Nam Tuan Ly; Atsuhiro Takasu | National Institute of Informatics, Tokyo, Japan + The Graduate University for Advanced Studies (SOKENDAI), Kanagawa, Japan; Tokyo University of Agriculture and Technology, Tokyo, Japan; National Institute of Informatics, Tokyo, Japan + The Graduate University for Advanced Studies (SOKENDAI), Kanagawa, Japan | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jirachanchaisiri_TRH2TQA_Table_Recognition_with_Hierarchical_Relationships_to_Table_Question-Answering_on_WACV_2025_paper.html | 0 | TRH2TQA: Table Recognition with Hierarchical Relationships to Table Question-Answering on Business Table Images
Despite advancements in visual question answering challenges persist with documents like financial reports often structured in complicated tabular structures with complex numerical computations. An alternativ... | [
-0.02965524047613144,
0.011611095629632473,
0.010346797294914722,
0.036367177963256836,
-0.005968233570456505,
-0.01051413081586361,
-0.0016303410520777106,
0.015915289521217346,
0.017105218023061752,
0.03614406660199165,
-0.03937918320298195,
-0.012801024131476879,
-0.009486888535320759,
... | |||
wacv_2025_a9952fa4b1 | a9952fa4b1 | wacv | 2,025 | TRNeRF: Restoring Blurry Rolling Shutter and Noisy Thermal Images with Neural Radiance Fields | Thermal cameras offer unique detection capabilities in building inspections search and rescue operations and autonomous vehicle perception. Of the different types of thermal cameras uncooled microbolometers are often chosen due to their relative affordability small size and low power consumption. However microbolometer... | Spencer Carmichael; Manohar Bhat; Mani Ramanagopal; Austin Buchan; Ram Vasudevan; Katherine A. Skinner | University of Michigan, Ann Arbor, MI USA; University of Michigan, Ann Arbor, MI USA; Carnegie Mellon University, Pittsburgh, PA USA; University of Michigan, Ann Arbor, MI USA; University of Michigan, Ann Arbor, MI USA; University of Michigan, Ann Arbor, MI USA | Poster | main | https://umautobots.github.io/trnerf | https://openaccess.thecvf.com/content/WACV2025/html/Carmichael_TRNeRF_Restoring_Blurry_Rolling_Shutter_and_Noisy_Thermal_Images_with_WACV_2025_paper.html | 0 | TRNeRF: Restoring Blurry Rolling Shutter and Noisy Thermal Images with Neural Radiance Fields
Thermal cameras offer unique detection capabilities in building inspections search and rescue operations and autonomous vehicle perception. Of the different types of thermal cameras uncooled microbolometers are often chosen du... | [
-0.045363061130046844,
-0.0068756816908717155,
-0.006693060509860516,
0.01746770180761814,
-0.01691070757806301,
0.022955462336540222,
0.030662069097161293,
0.010226777754724026,
0.014381405897438526,
0.03155691176652908,
-0.023539850488305092,
-0.031027311459183693,
-0.023959878832101822,
... | ||
wacv_2025_553d8eccf1 | 553d8eccf1 | wacv | 2,025 | TRUST: Time-Domain Residual Unsupervised Stability Technique for Improved Heart Rate Estimation | Camera-based estimation of vital signs is a promising method for non-contact health monitoring which analyzes minute changes in video data. However the creation of accurate models for this task is challenging due to the scarcity of datasets that possess synchronized vital sign recordings. Our research enhances an exist... | Shahzad Ahmad; Sania Bano; Sukalpa Chanda; Santosh Kumar Vipparthi; Subrahmanyam Murala | Østfold University College, Norway; Indian Institute of Technology Ropar, India; Østfold University College, Norway; Indian Institute of Technology Ropar, India; Trinity College Dublin, Ireland | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ahmad_TRUST_Time-Domain_Residual_Unsupervised_Stability_Technique_for_Improved_Heart_Rate_WACV_2025_paper.html | 0 | TRUST: Time-Domain Residual Unsupervised Stability Technique for Improved Heart Rate Estimation
Camera-based estimation of vital signs is a promising method for non-contact health monitoring which analyzes minute changes in video data. However the creation of accurate models for this task is challenging due to the scar... | [
-0.03800588473677635,
-0.040678173303604126,
-0.025646548718214035,
0.0067595914006233215,
0.010958239436149597,
0.014326437376439571,
0.044055648148059845,
0.019578225910663605,
-0.012479959987103939,
0.03091689571738243,
-0.03449850529432297,
-0.005892025772482157,
0.0023185352329164743,
... | |||
wacv_2025_cac9b53ebc | cac9b53ebc | wacv | 2,025 | TaCOS: Task-Specific Camera Optimization with Simulation | The performance of perception tasks is heavily influenced by imaging systems. However designing cameras with high task performance is costly requiring extensive camera knowledge and experimentation with physical hardware. Additionally cameras and perception tasks are mostly designed in isolation whereas recent methods ... | Chengyang Yan; Donald G. Dansereau | ; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yan_TaCOS_Task-Specific_Camera_Optimization_with_Simulation_WACV_2025_paper.html | 0 | 2404.11031 | TaCOS: Task-Specific Camera Optimization with Simulation
The performance of perception tasks is heavily influenced by imaging systems. However designing cameras with high task performance is costly requiring extensive camera knowledge and experimentation with physical hardware. Additionally cameras and perception tasks... | [
-0.04227227345108986,
-0.005032626911997795,
-0.016081061214208603,
0.007573632523417473,
-0.01987910084426403,
0.018640024587512016,
-0.011789186857640743,
0.01443793810904026,
0.010092190466821194,
0.05627922713756561,
-0.02456604316830635,
-0.009064115583896637,
0.03340119868516922,
0.0... | ||
wacv_2025_5b350ae4c2 | 5b350ae4c2 | wacv | 2,025 | Talking Head Anime 4: Distillation for Real-Time Performance | We study the problem of creating a character model that can be controlled in real time from a single image of an anime character. A solution would greatly reduce the cost of creating avatars computer games and other interactive applications. Talking Head Anime 3 (THA3) is an open source project that attempts to directl... | Pramook Khungurn | pixiv Inc., Tokyo, Japan | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Khungurn_Talking_Head_Anime_4_Distillation_for_Real-Time_Performance_WACV_2025_paper.html | 0 | Talking Head Anime 4: Distillation for Real-Time Performance
We study the problem of creating a character model that can be controlled in real time from a single image of an anime character. A solution would greatly reduce the cost of creating avatars computer games and other interactive applications. Talking Head Anim... | [
0.0032285472843796015,
-0.05504347383975983,
0.009108783677220345,
0.014095818623900414,
-0.024283885955810547,
-0.03773771598935127,
0.004198506940156221,
0.009620512835681438,
0.0002215555723523721,
-0.0018271065782755613,
-0.00012509748921729624,
-0.03170861303806305,
0.005982581991702318... | |||
wacv_2025_a63a7ff49e | a63a7ff49e | wacv | 2,025 | Task Configuration Impacts Annotation Quality and Model Training Performance in Crowdsourced Image Segmentation | Many industrial image segmentation systems require training on large annotated datasets but there is little standardization for producing training annotations. Data is often obtained via crowdsourcing but many labeling task configurations are set by convenience and may have unintended effects on data quality. In this w... | Benjamin R Bauchwitz; Mary Cummings | Duke University Department of Computer Science; George Mason University College of Engineering and Computing | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Bauchwitz_Task_Configuration_Impacts_Annotation_Quality_and_Model_Training_Performance_in_WACV_2025_paper.html | 0 | Task Configuration Impacts Annotation Quality and Model Training Performance in Crowdsourced Image Segmentation
Many industrial image segmentation systems require training on large annotated datasets but there is little standardization for producing training annotations. Data is often obtained via crowdsourcing but man... | [
-0.07632608711719513,
-0.03837926685810089,
-0.05499226227402687,
0.01319850329309702,
-0.01382914837449789,
-0.011297558434307575,
0.027802444994449615,
0.026505116373300552,
-0.010847097262740135,
0.015414770692586899,
-0.0012939488515257835,
-0.03470350429415703,
0.0032005244866013527,
... | |||
wacv_2025_91d1ab7ef6 | 91d1ab7ef6 | wacv | 2,025 | TaxaBind: A Unified Embedding Space for Ecological Applications | We present TaxaBind a unified embedding space for characterizing any species of interest. TaxaBind is a multimodal embedding space across six modalities: ground-level images of species geographic location satellite image text audio and environmental features useful for solving ecological problems. To learn this joint e... | Srikumar Sastry; Subash Khanal; Aayush Dhakal; Adeel Ahmad; Nathan Jacobs | Washington University in St. Louis; Washington University in St. Louis; Washington University in St. Louis; Washington University in St. Louis; Washington University in St. Louis | Poster | main | https://github.com/mvrl/TaxaBind | https://openaccess.thecvf.com/content/WACV2025/html/Sastry_TaxaBind_A_Unified_Embedding_Space_for_Ecological_Applications_WACV_2025_paper.html | 7 | 2411.00683 | TaxaBind: A Unified Embedding Space for Ecological Applications
We present TaxaBind a unified embedding space for characterizing any species of interest. TaxaBind is a multimodal embedding space across six modalities: ground-level images of species geographic location satellite image text audio and environmental featur... | [
-0.03893326222896576,
-0.04101249948143959,
-0.054327256977558136,
0.014354375191032887,
-0.019180497154593468,
-0.02939547225832939,
0.055433642119169235,
-0.01674836128950119,
-0.019762303680181503,
0.021574482321739197,
-0.04498022049665451,
-0.008889220654964447,
-0.0005683927447535098,
... | |
wacv_2025_1485cadd5f | 1485cadd5f | wacv | 2,025 | TempA-VLP: Temporal-Aware Vision-Language Pretraining for Longitudinal Exploration in Chest X-ray Image | Longitudinal medical image processing is a significant task to understand the dynamic changes of disease by taking and comparing image series over time providing insights into how conditions evolve and enabling more accurate diagnosis and treatment planning. While recent advancements in biomedical Vision-Language Pre-t... | Zhuoyi Yang; Liyue Shen | University of Michigan; University of Michigan | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yang_TempA-VLP_Temporal-Aware_Vision-Language_Pretraining_for_Longitudinal_Exploration_in_Chest_X-ray_WACV_2025_paper.html | 1 | TempA-VLP: Temporal-Aware Vision-Language Pretraining for Longitudinal Exploration in Chest X-ray Image
Longitudinal medical image processing is a significant task to understand the dynamic changes of disease by taking and comparing image series over time providing insights into how conditions evolve and enabling more ... | [
-0.07605059444904327,
-0.026088379323482513,
-0.02284758724272251,
0.015852876007556915,
-0.05196070671081543,
0.03055347129702568,
-0.036134835332632065,
0.032587967813014984,
0.019840851426124573,
-0.002381082158535719,
0.009470315650105476,
-0.012288005091249943,
0.02270355075597763,
0.... | |||
wacv_2025_6a42bf9d99 | 6a42bf9d99 | wacv | 2,025 | Temporal Dynamics in Visual Data: Analyzing the Impact of Time on Classification Accuracy | Visual datasets are generally constructed from the samples available at the time of their collection and are not further updated. However these static datasets do not reflect the distribution changes that occur in real data. We analyze how different collection times lead to a shift in class distribution by collecting a... | Tom Pégeot; Eva Feillet; Adrian Popescu; Inna Kucher; Bertrand Delezoide | Université Paris-Saclay, CEA, LIST; Université Paris-Saclay, CEA, LIST + Université Paris-Saclay, CentraleSupélec, MICS; Université Paris-Saclay, CEA, LIST; Université Paris-Saclay, CEA, LIST; Amanda | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Pegeot_Temporal_Dynamics_in_Visual_Data_Analyzing_the_Impact_of_Time_WACV_2025_paper.html | 0 | Temporal Dynamics in Visual Data: Analyzing the Impact of Time on Classification Accuracy
Visual datasets are generally constructed from the samples available at the time of their collection and are not further updated. However these static datasets do not reflect the distribution changes that occur in real data. We an... | [
-0.06769631057977676,
-0.04913562163710594,
-0.03792109340429306,
0.027766646817326546,
-0.0020353063009679317,
-0.02893831394612789,
-0.00325463037006557,
0.021071406081318855,
-0.006769631057977676,
0.024902570992708206,
0.004038066603243351,
-0.03193257376551628,
-0.03820006176829338,
0... | |||
wacv_2025_0d3f0ec46e | 0d3f0ec46e | wacv | 2,025 | Temporally Grounding Instructional Diagrams in Unconstrained Videos | We study the challenging problem of simultaneously localizing a sequence of queries in the form of instructional diagrams in a video. This requires understanding not only the individual queries but also their interrelationships. However most existing methods focus on grounding one query at a time ignoring the inherent ... | Jiahao Zhang; Frederic Z. Zhang; Cristian Rodriguez; Yizhak Ben-Shabat; Anoop Cherian; Stephen Gould | ;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_Temporally_Grounding_Instructional_Diagrams_in_Unconstrained_Videos_WACV_2025_paper.html | 2 | 2407.12066 | Temporally Grounding Instructional Diagrams in Unconstrained Videos
We study the challenging problem of simultaneously localizing a sequence of queries in the form of instructional diagrams in a video. This requires understanding not only the individual queries but also their interrelationships. However most existing m... | [
-0.03019043616950512,
-0.038615237921476364,
-0.021634289994835854,
-0.011361286044120789,
-0.006829905789345503,
0.018153665587306023,
0.009180031716823578,
-0.007317756302654743,
-0.05317569524049759,
0.04308094456791878,
-0.003841822035610676,
-0.04867246001958847,
0.031729042530059814,
... | ||
wacv_2025_babf74e881 | babf74e881 | wacv | 2,025 | Temporally Streaming Audio-Visual Synchronization for Real-World Videos | We introduce RealSync a novel dataset designed to significantly enhance the training and evaluation of models for audio-visual synchronization (AV Sync) tasks. Sourced from high-quality YouTube channels RealSync covers a wide range of content domains providing an improved scale diversity and alignment with broadcast co... | Jordan G Voas; Wei-Cheng Tseng; Layne Berry; Xixi Hu; Puyuan Peng; James Stuedemann; David Harwath | The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin | Poster | main | https://github.com/jvoas655/StreamSync | https://openaccess.thecvf.com/content/WACV2025/html/Voas_Temporally_Streaming_Audio-Visual_Synchronization_for_Real-World_Videos_WACV_2025_paper.html | 0 | Temporally Streaming Audio-Visual Synchronization for Real-World Videos
We introduce RealSync a novel dataset designed to significantly enhance the training and evaluation of models for audio-visual synchronization (AV Sync) tasks. Sourced from high-quality YouTube channels RealSync covers a wide range of content domai... | [
-0.032644595950841904,
-0.04969334974884987,
-0.030382463708519936,
0.013627969659864902,
-0.018906278535723686,
0.004119656048715115,
0.02431332692503929,
0.024386892095208168,
-0.0012977375881746411,
0.048553090542554855,
0.015301579609513283,
-0.02832263521850109,
-0.00768757238984108,
... | ||
wacv_2025_9e1bb15a0e | 9e1bb15a0e | wacv | 2,025 | Test-Time Adaptation in Point Clouds: Leveraging Sampling Variation with Weight Averaging | Test-Time Adaptation (TTA) addresses distribution shifts during testing by adapting a pretrained model without access to source data. In this work we propose a novel TTA approach for 3D point cloud classification combining sampling variation with weight averaging. Our method leverages Farthest Point Sampling (FPS) and ... | Ali Bahri; Moslem Yazdanpanah; Mehrdad Noori; Sahar Dastani Oghani; Milad Cheraghalikhani; David Osowiechi; Farzad Beizaee; Gustavo A. Vargas Hakim; Ismail Ben Ayed; Christian Desrosiers | ;;;;;;;;; | Poster | main | https://github.com/AliBahri94/SVWA_TTA | https://openaccess.thecvf.com/content/WACV2025/html/Bahri_Test-Time_Adaptation_in_Point_Clouds_Leveraging_Sampling_Variation_with_Weight_WACV_2025_paper.html | 0 | 2411.01116 | Test-Time Adaptation in Point Clouds: Leveraging Sampling Variation with Weight Averaging
Test-Time Adaptation (TTA) addresses distribution shifts during testing by adapting a pretrained model without access to source data. In this work we propose a novel TTA approach for 3D point cloud classification combining samplin... | [
-0.011268001049757004,
-0.003722304245457053,
-0.029904231429100037,
-0.0003375233500264585,
-0.029508864507079124,
-0.0228594858199358,
0.010809732601046562,
0.027603905647993088,
0.01763882488012314,
0.028790012001991272,
-0.018941743299365044,
0.017045771703124046,
-0.026723314076662064,
... | |
wacv_2025_0b3378ae6d | 0b3378ae6d | wacv | 2,025 | Test-Time Adaptation of 3D Point Clouds via Denoising Diffusion Models | Test-time adaptation (TTA) of 3D point clouds is crucial for mitigating discrepancies between training and testing samples in real-world scenarios particularly when handling corrupted point clouds. LiDAR data for instance can be affected by sensor failures or environmental factors causing domain gaps. Adapting models t... | Hamidreza Dastmalchi; Aijun An; Ali Cheraghian; Shafin Rahman; Sameera Ramasinghe | York University, Canada; York University, Canada; Data61-CSIRO, Australia+Australian National University; North South University, Bangladesh; University of Adelaide, Australia | Poster | main | https://github.com/hamidreza-dastmalchi/3DD-TTA | https://openaccess.thecvf.com/content/WACV2025/html/Dastmalchi_Test-Time_Adaptation_of_3D_Point_Clouds_via_Denoising_Diffusion_Models_WACV_2025_paper.html | 1 | 2411.14495 | Test-Time Adaptation of 3D Point Clouds via Denoising Diffusion Models
Test-time adaptation (TTA) of 3D point clouds is crucial for mitigating discrepancies between training and testing samples in real-world scenarios particularly when handling corrupted point clouds. LiDAR data for instance can be affected by sensor f... | [
-0.009822795167565346,
0.002388725057244301,
-0.030522102490067482,
0.001990232151001692,
-0.01272498443722725,
-0.006657176185399294,
-0.007206359878182411,
0.02253885008394718,
-0.0004498393682297319,
0.05093565583229065,
-0.024003339931368828,
-0.010510390624403954,
-0.016421927139163017,... | |
wacv_2025_4fa5a6b9e9 | 4fa5a6b9e9 | wacv | 2,025 | Test-Time Low Rank Adaptation via Confidence Maximization for Zero-Shot Generalization of Vision-Language Models | The conventional modus operandi for adapting pre-trained vision-language models (VLMs) during test-time involves tuning learnable prompts i.e. test-time prompt tuning. This paper introduces Test-Time Low-rank adaptation (TTL) as an alternative to prompt tuning for zero-shot generalization of large-scale VLMs. Taking in... | Raza Imam; Hanan Gani; Muhammad Huzaifa; Karthik Nandakumar | ;;; | Poster | main | https://github.com/Razaimam45/TTL-Test-Time-Low-Rank-Adaptation | https://openaccess.thecvf.com/content/WACV2025/html/Imam_Test-Time_Low_Rank_Adaptation_via_Confidence_Maximization_for_Zero-Shot_Generalization_WACV_2025_paper.html | 4 | 2407.15913 | Test-Time Low Rank Adaptation via Confidence Maximization for Zero-Shot Generalization of Vision-Language Models
The conventional modus operandi for adapting pre-trained vision-language models (VLMs) during test-time involves tuning learnable prompts i.e. test-time prompt tuning. This paper introduces Test-Time Low-ran... | [
-0.0435967892408371,
-0.014121255837380886,
-0.0025695464573800564,
0.04204876348376274,
0.012996235862374306,
-0.0034335621166974306,
0.02910652756690979,
-0.0019856609869748354,
0.01525527611374855,
0.024624446406960487,
-0.025758467614650726,
-0.025236457586288452,
-0.01879234053194523,
... | |
wacv_2025_656c3c9f0c | 656c3c9f0c | wacv | 2,025 | Text Change Detection in Multilingual Documents using Image Comparison | Document comparison typically relies on optical character recognition (OCR) as its core technology. However OCR requires the selection of appropriate language models for each document and the performance of multilingual or hybrid models remains limited. To overcome these challenges we propose text change detection (TCD... | Doyoung Park; Naresh Reddy Yarram; Sunjin Kim; MinKyu Kim; Seongho Joe; Taehee Lee | Samsung SDS; Samsung SDS; Samsung SDS; Samsung SDS; Samsung SDS; Samsung SDS | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Park_Text_Change_Detection_in_Multilingual_Documents_using_Image_Comparison_WACV_2025_paper.html | 1 | 2412.04137 | Text Change Detection in Multilingual Documents using Image Comparison
Document comparison typically relies on optical character recognition (OCR) as its core technology. However OCR requires the selection of appropriate language models for each document and the performance of multilingual or hybrid models remains limi... | [
-0.08818170428276062,
-0.024297183379530907,
-0.020175015553832054,
0.01924888975918293,
0.01413703802973032,
0.0005010840250179172,
-0.0046669477596879005,
0.021900150924921036,
0.03708134964108467,
0.0010191923938691616,
-0.02998105250298977,
-0.08157170563936234,
-0.019721031188964844,
... | ||
wacv_2025_36723b8a63 | 36723b8a63 | wacv | 2,025 | Text-to-Image Synthesis for Domain Generalization in Face Anti-Spoofing | This paper addresses the challenge of developing robust Face Anti-Spoofing (FAS) models for face recognition systems. Traditional FAS protocols are limited by a lack of diversity in subject identities and environmental conditions restricting generalization to real-world scenarios. Recent advancements in spoof image syn... | Naeun Ko; Yonghyun Jeong; Jong Chul Ye | NA VER Cloud, South Korea + Kim Jaechul Graduate School of AI, KAIST, South Korea; NA VER Cloud, South Korea; Kim Jaechul Graduate School of AI, KAIST, South Korea | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ko_Text-to-Image_Synthesis_for_Domain_Generalization_in_Face_Anti-Spoofing_WACV_2025_paper.html | 0 | Text-to-Image Synthesis for Domain Generalization in Face Anti-Spoofing
This paper addresses the challenge of developing robust Face Anti-Spoofing (FAS) models for face recognition systems. Traditional FAS protocols are limited by a lack of diversity in subject identities and environmental conditions restricting genera... | [
-0.04254808649420738,
-0.01056385226547718,
-0.0241276565939188,
-0.007335246540606022,
-0.013902212493121624,
-0.053194254636764526,
-0.021621599793434143,
0.048365067690610886,
0.04298710450530052,
0.02734711579978466,
-0.02639591135084629,
0.0056569199077785015,
-0.005958744324743748,
0... | |||
wacv_2025_31acd9b8d0 | 31acd9b8d0 | wacv | 2,025 | Texture Shape and Order Matter: A New Transformer Design for Sequential DeepFake Detection | Sequential DeepFake detection is an emerging task that predicts the manipulation sequence in order. Existing methods typically formulate it as an image-to-sequence problem employing conventional Transformer architectures. However these methods lack dedicated design and consequently result in limited performance. As suc... | Yunfei Li; Yuezun Li; Xin Wang; Baoyuan Wu; Jiaran Zhou; Junyu Dong | ;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Li_Texture_Shape_and_Order_Matter_A_New_Transformer_Design_for_WACV_2025_paper.html | 0 | 2404.13873 | Texture Shape and Order Matter: A New Transformer Design for Sequential DeepFake Detection
Sequential DeepFake detection is an emerging task that predicts the manipulation sequence in order. Existing methods typically formulate it as an image-to-sequence problem employing conventional Transformer architectures. However... | [
-0.032778628170490265,
-0.04776690527796745,
-0.032985489815473557,
0.015467826277017593,
0.00619653332978487,
0.01985899545252323,
-0.015749914571642876,
0.01494126208126545,
0.013634254224598408,
0.06070534139871597,
-0.026365825906395912,
-0.01302306354045868,
0.02433479204773903,
-0.00... | ||
wacv_2025_d9b40f3b13 | d9b40f3b13 | wacv | 2,025 | The FineView Dataset:A 3D Scanned Multi-View Object Dataset of Fine-Grained Category Instances | In the past decade state-of-the-art deep learning models have shown impressive performance in many computer vision tasks by learning from large and diverse image datasets. Most of these datasets consist of web-scraped image collections. This approach however makes it very challenging to obtain desirable data such as mu... | Suguru Onda; Ryan Farrell | Brigham Young University; Brigham Young University | Poster | main | https://github.com/byu-vision/fineview | https://openaccess.thecvf.com/content/WACV2025/html/Onda_The_FineView_DatasetA_3D_Scanned_Multi-View_Object_Dataset_of_Fine-Grained_WACV_2025_paper.html | 0 | The FineView Dataset:A 3D Scanned Multi-View Object Dataset of Fine-Grained Category Instances
In the past decade state-of-the-art deep learning models have shown impressive performance in many computer vision tasks by learning from large and diverse image datasets. Most of these datasets consist of web-scraped image c... | [
-0.052854590117931366,
-0.04956260696053505,
-0.03840645030140877,
-0.00039035125519149005,
-0.0033102701418101788,
0.02719542384147644,
-0.014823060482740402,
0.021690499037504196,
-0.0189288929104805,
0.02050172910094261,
-0.009318135678768158,
0.012372363358736038,
0.0007829886162653565,
... | ||
wacv_2025_714bf845ee | 714bf845ee | wacv | 2,025 | Through the Curved Cover: Synthesizing Cover Aberrated Scenes with Refractive Field | Recent extended reality headsets and field robots have adopted covers to protect the front-facing cameras from environmental hazards and falls. The surface irregularities on the cover can lead to optical aberrations like blurring and non-parametric distortions. Novel view synthesis methods like NeRF and 3D Gaussian Spl... | Liuyue Xie; Jiancong Guo; László A. Jeni; Zhiheng Jia; Mingyang Li; Yunwen Zhou; Chao Guo | Carnegie Mellon University; Google; Carnegie Mellon University; Google; Google; Google; Google | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Xie_Through_the_Curved_Cover_Synthesizing_Cover_Aberrated_Scenes_with_Refractive_WACV_2025_paper.html | 0 | 2411.06365 | Through the Curved Cover: Synthesizing Cover Aberrated Scenes with Refractive Field
Recent extended reality headsets and field robots have adopted covers to protect the front-facing cameras from environmental hazards and falls. The surface irregularities on the cover can lead to optical aberrations like blurring and no... | [
-0.043996408581733704,
0.0025010639801621437,
-0.000369580986443907,
-0.005908647086471319,
-0.01522022858262062,
-0.017897948622703552,
-0.02761397697031498,
0.03971949592232704,
0.01628945767879486,
0.038678161799907684,
-0.043103836476802826,
0.004318751394748688,
0.0042559923604130745,
... | ||
wacv_2025_05b858d354 | 05b858d354 | wacv | 2,025 | TimberVision: A Multi-Task Dataset and Framework for Log-Component Segmentation and Tracking in Autonomous Forestry Operations | Timber represents an increasingly valuable and versatile resource. However forestry operations such as harvesting handling and measuring logs still require substantial human labor in remote environments posing significant safety risks. Progressively automating these tasks has the potential of increasing their efficienc... | Daniel Steininger; Julia Simon; Andreas Trondl; Markus Murschitz | AIT Austrian Institute of Technology (Center for Vision, Automation & Control); AIT Austrian Institute of Technology (Center for Vision, Automation & Control); AIT Austrian Institute of Technology (Center for Vision, Automation & Control); AIT Austrian Institute of Technology (Center for Vision, Automation & Control) | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Steininger_TimberVision_A_Multi-Task_Dataset_and_Framework_for_Log-Component_Segmentation_and_WACV_2025_paper.html | 0 | 2501.07360 | TimberVision: A Multi-Task Dataset and Framework for Log-Component Segmentation and Tracking in Autonomous Forestry Operations
Timber represents an increasingly valuable and versatile resource. However forestry operations such as harvesting handling and measuring logs still require substantial human labor in remote env... | [
-0.01724540814757347,
-0.009381097741425037,
-0.016528382897377014,
0.012842129915952682,
-0.016592729836702347,
-0.03704637289047241,
-0.004221723880618811,
0.012814552523195744,
0.010810554958879948,
0.039344534277915955,
0.004775580950081348,
-0.020977623760700226,
0.010258995927870274,
... | ||
wacv_2025_c77ed30595 | c77ed30595 | wacv | 2,025 | To Ask or Not to Ask? Detecting Absence of Information in Vision and Language Navigation | Recent research in Vision Language Navigation (VLN) has overlooked the development of agents' inquisitive abilities which allow them to ask clarifying questions when instructions are incomplete. This paper addresses how agents can recognize "when" they lack sufficient information without focusing on "what" is missing p... | Savitha Sam Abraham; Sourav Garg; Feras Dayoub | Australian Institute for Machine Learning; Australian Institute for Machine Learning; Australian Institute for Machine Learning | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Abraham_To_Ask_or_Not_to_Ask_Detecting_Absence_of_Information_WACV_2025_paper.html | 0 | 2411.05831 | To Ask or Not to Ask? Detecting Absence of Information in Vision and Language Navigation
Recent research in Vision Language Navigation (VLN) has overlooked the development of agents' inquisitive abilities which allow them to ask clarifying questions when instructions are incomplete. This paper addresses how agents can ... | [
-0.03658434376120567,
-0.04609627276659012,
-0.010133863426744938,
0.013325847685337067,
-0.002590628806501627,
-0.04188907518982887,
0.032852742820978165,
-0.011487483978271484,
0.009274131618440151,
0.00800282508134842,
-0.008574455976486206,
-0.04675479233264923,
-0.01774340681731701,
0... | ||
wacv_2025_5ed3e41560 | 5ed3e41560 | wacv | 2,025 | Token Turing Machines are Efficient Vision Models | We propose Vision Token Turing Machines (ViTTM) an efficient low-latency memory-augmented Vision Transformer (ViT). Our approach builds on Neural Turing Machines (NTM) and Token Turing Machines (TTM) which were applied to NLP and sequential visual understanding tasks. ViTTMs are designed for non-sequential computer vis... | Purvish Jajal; Nick Eliopoulous; Benjamin Shiue-Hal Chou; George K. Thiravathukal; James C. Davis; Yung-Hsiang Lu | ;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jajal_Token_Turing_Machines_are_Efficient_Vision_Models_WACV_2025_paper.html | 0 | Token Turing Machines are Efficient Vision Models
We propose Vision Token Turing Machines (ViTTM) an efficient low-latency memory-augmented Vision Transformer (ViT). Our approach builds on Neural Turing Machines (NTM) and Token Turing Machines (TTM) which were applied to NLP and sequential visual understanding tasks. V... | [
-0.0134030282497406,
-0.030699988827109337,
-0.003242592327296734,
0.04206199571490288,
-0.005920846480876207,
0.03256230428814888,
0.006692108698189259,
0.03848785534501076,
0.00893535278737545,
0.030587121844291687,
-0.014992580749094486,
-0.018529098480939865,
-0.00617950176820159,
0.03... | |||
wacv_2025_e3d82a5856 | e3d82a5856 | wacv | 2,025 | TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm | Text-Video Retrieval (TVR) methods typically match query-candidate pairs by aligning text and video features in coarse-grained fine-grained or combined (coarse-to-fine) manners. However these frameworks predominantly employ a one(query)-to-one(candidate) alignment paradigm which struggles to discern nuanced differences... | Bingqing Zhang; Zhuo Cao; Heming Du; Xin Yu; Xue Li; Jiajun Liu; Sen Wang | The University of Queensland, Australia+CSIRO Data61, Australia; The University of Queensland, Australia+CSIRO Data61, Australia; The University of Queensland, Australia; The University of Queensland, Australia; The University of Queensland, Australia; CSIRO Data61, Australia+The University of Queensland, Australia; Th... | Poster | main | https://github.com/bingqingzhang/TokenBinder | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_TokenBinder_Text-Video_Retrieval_with_One-to-Many_Alignment_Paradigm_WACV_2025_paper.html | 0 | 2409.19865 | TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm
Text-Video Retrieval (TVR) methods typically match query-candidate pairs by aligning text and video features in coarse-grained fine-grained or combined (coarse-to-fine) manners. However these frameworks predominantly employ a one(query)-to-one(candid... | [
-0.024699131026864052,
-0.042178232222795486,
-0.024735968559980392,
0.028290728107094765,
-0.0018153677228838205,
0.04066792130470276,
0.031237678602337837,
0.01060902327299118,
-0.020554982125759125,
0.0048394459299743176,
-0.016825247555971146,
-0.01765407808125019,
-0.03993118554353714,
... | |
wacv_2025_162a071be1 | 162a071be1 | wacv | 2,025 | Towards Accurate Unified Anomaly Segmentation | Unsupervised anomaly detection (UAD) from images strives to model normal data distributions creating discriminative representations to distinguish and precisely localize anomalies. Despite recent advancements in the efficient and unified one-for-all scheme challenges persist in accurately segmenting anomalies for furth... | Wenxin Ma; Qingsong Yao; Xiang Zhang; Zhelong Huang; Zihang Jiang; S.Kevin Zhou | ;;;;; | Poster | main | https://github.com/Mwxinnn/UniAS | https://openaccess.thecvf.com/content/WACV2025/html/Ma_Towards_Accurate_Unified_Anomaly_Segmentation_WACV_2025_paper.html | 1 | 2501.12295 | Towards Accurate Unified Anomaly Segmentation
Unsupervised anomaly detection (UAD) from images strives to model normal data distributions creating discriminative representations to distinguish and precisely localize anomalies. Despite recent advancements in the efficient and unified one-for-all scheme challenges persis... | [
-0.0684976652264595,
-0.002105009974911809,
-0.06937819719314575,
-0.005764700472354889,
-0.038743190467357635,
0.003941734321415424,
-0.0033914048690348864,
0.011923803947865963,
-0.020967550575733185,
0.06769051402807236,
-0.032744601368904114,
-0.017417926341295242,
0.016546571627259254,
... | |
wacv_2025_a0523a565e | a0523a565e | wacv | 2,025 | Towards Generalized Face Anti-Spoofing from a Frequency Shortcut View | The generalization capability of a face anti-spoofing (FAS) model is critical to its practicality in the real world. Recent studies have theoretically and empirically uncovered that neural networks tend to exploit easy-to-learn frequency sets for decisions. These simplicity-biased representations depending on what best... | Junyi Cao; Chao Ma | MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University; MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University | Poster | main | https://github.com/VISION-SJTU/UniDefense | https://openaccess.thecvf.com/content/WACV2025/html/Cao_Towards_Generalized_Face_Anti-Spoofing_from_a_Frequency_Shortcut_View_WACV_2025_paper.html | 0 | Towards Generalized Face Anti-Spoofing from a Frequency Shortcut View
The generalization capability of a face anti-spoofing (FAS) model is critical to its practicality in the real world. Recent studies have theoretically and empirically uncovered that neural networks tend to exploit easy-to-learn frequency sets for dec... | [
-0.057159386575222015,
-0.037945836782455444,
-0.0485706701874733,
-0.004845035262405872,
0.005830701440572739,
-0.062009047716856,
0.03054177016019821,
0.03405870124697685,
0.012022350914776325,
0.060083989053964615,
-0.053494371473789215,
-0.01799187809228897,
-0.010245375335216522,
-0.0... | ||
wacv_2025_adaf5925ec | adaf5925ec | wacv | 2,025 | Towards High-Fidelity Head Blending with Chroma Keying for Industrial Applications | We introduce an industrial Head Blending pipeline for the task of seamlessly integrating an actor's head onto a target body in digital content creation. The key challenge stems from discrepancies in head shape and hair structure which lead to unnatural boundaries and blending artifacts. Existing methods treat foregroun... | Hah Min Lew; Sahng-Min Yoo; Hyunwoo Kang; Gyeong-Moon Park | Klleon AI Research; Samsung Research + Klleon AI Research; Hyperconnect + Klleon AI Research; Kyung Hee University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lew_Towards_High-Fidelity_Head_Blending_with_Chroma_Keying_for_Industrial_Applications_WACV_2025_paper.html | 0 | 2411.00652 | Towards High-Fidelity Head Blending with Chroma Keying for Industrial Applications
We introduce an industrial Head Blending pipeline for the task of seamlessly integrating an actor's head onto a target body in digital content creation. The key challenge stems from discrepancies in head shape and hair structure which le... | [
-0.06305290758609772,
-0.030883805826306343,
-0.04076221585273743,
0.014064800925552845,
-0.009065921418368816,
-0.012026689946651459,
-0.017480013892054558,
0.03955036774277687,
-0.00917149893939495,
-0.00016912532737478614,
-0.02772565186023712,
-0.01988535188138485,
-0.0178105179220438,
... | ||
wacv_2025_8d9fdca6f6 | 8d9fdca6f6 | wacv | 2,025 | Towards On-the-Fly Novel Category Discovery in Dynamic Long-Tailed Distributions | As the diversity of real-world object categories increases the need for sophisticated classification methods also grows. However Novel Category Discovery (NCD) which aims to predict unseen categories often falls short in scenarios where new categories are constantly updated and data distributions are potentially biased... | Hoin Jung; Xiaoqian Wang | ; | Poster | main | https://github.com/HoinJung/NCD-DLT | https://openaccess.thecvf.com/content/WACV2025/html/Jung_Towards_On-the-Fly_Novel_Category_Discovery_in_Dynamic_Long-Tailed_Distributions_WACV_2025_paper.html | 0 | Towards On-the-Fly Novel Category Discovery in Dynamic Long-Tailed Distributions
As the diversity of real-world object categories increases the need for sophisticated classification methods also grows. However Novel Category Discovery (NCD) which aims to predict unseen categories often falls short in scenarios where ne... | [
-0.0725504457950592,
-0.03907667472958565,
-0.03720904141664505,
0.041590798646211624,
-0.016943402588367462,
0.005306598264724016,
-0.007304429076611996,
0.0072325970977544785,
-0.023040153086185455,
0.027511702850461006,
-0.029540961608290672,
-0.028194108977913857,
-0.04313519224524498,
... | ||
wacv_2025_2c82ed6d28 | 2c82ed6d28 | wacv | 2,025 | Towards Privacy-Preserving Split Learning for ControlNet | With the emerging trend of large generative models ControlNet is introduced to enable users to fine-tune pre-trained models with their own data for various use cases. A natural question arises: how can we train ControlNet models while ensuring users' data privacy across distributed devices? We first propose a new distr... | Dixi Yao | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yao_Towards_Privacy-Preserving_Split_Learning_for_ControlNet_WACV_2025_paper.html | 0 | Towards Privacy-Preserving Split Learning for ControlNet
With the emerging trend of large generative models ControlNet is introduced to enable users to fine-tune pre-trained models with their own data for various use cases. A natural question arises: how can we train ControlNet models while ensuring users' data privacy... | [
-0.044526029378175735,
-0.007678336463868618,
-0.04667097330093384,
0.007867868058383465,
-0.046966828405857086,
-0.019914673641324043,
0.014025329612195492,
0.014154765754938126,
0.012342660687863827,
0.03160090744495392,
-0.04090182110667229,
0.0020848463755100965,
-0.038165170699357986,
... | ||||
wacv_2025_f2f6ecaebe | f2f6ecaebe | wacv | 2,025 | Towards Real-Time Open-Vocabulary Video Instance Segmentation | In this paper we address the challenge of performing open-vocabulary video instance segmentation (OV-VIS) in real-time. We analyze the computational bottlenecks of state-of-the-art foundation models that performs OV-VIS and propose a new method TROY-VIS that significantly improves processing speed while maintaining hig... | Bin Yan; Martin Sundermeyer; David Joseph Tan; Huchuan Lu; Federico Tombari | Dalian University of Technology; Google; Google; Dalian University of Technology; Google+TU Munich | Poster | main | https://github.com/google-research/troyvis | https://openaccess.thecvf.com/content/WACV2025/html/Yan_Towards_Real-Time_Open-Vocabulary_Video_Instance_Segmentation_WACV_2025_paper.html | 2 | 2412.04434 | Towards Real-Time Open-Vocabulary Video Instance Segmentation
In this paper we address the challenge of performing open-vocabulary video instance segmentation (OV-VIS) in real-time. We analyze the computational bottlenecks of state-of-the-art foundation models that performs OV-VIS and propose a new method TROY-VIS that... | [
-0.002477461937814951,
-0.026078546419739723,
-0.008299383334815502,
0.03175177425146103,
0.007343169767409563,
0.04106684774160385,
0.01771511137485504,
0.009507231414318085,
0.033490344882011414,
0.041213251650333405,
-0.018620997667312622,
-0.03098314255475998,
0.04190868139266968,
0.01... | |
wacv_2025_94c3cd8758 | 94c3cd8758 | wacv | 2,025 | Towards Robust Training via Gradient-Diversified Backpropagation | Neural networks are prone to be vulnerable to adversarial attacks and domain shifts. Adversarial-driven methods including adversarial training and adversarial augmentation have been frequently proposed to improve the model's robustness against adversarial attacks and distribution-shifted samples. Nonetheless recent res... | Xilin He; Cheng Luo; Qinliang Lin; Weicheng Xie; Muhammad Haris Khan; Siyang Song; Linlin Shen | Shenzhen University, China; Monash University, Australia; Shenzhen University, China; Shenzhen University, China; MBZUAI, UAE; University of Exeter, England; Shenzhen University, China | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/He_Towards_Robust_Training_via_Gradient-Diversified_Backpropagation_WACV_2025_paper.html | 0 | Towards Robust Training via Gradient-Diversified Backpropagation
Neural networks are prone to be vulnerable to adversarial attacks and domain shifts. Adversarial-driven methods including adversarial training and adversarial augmentation have been frequently proposed to improve the model's robustness against adversarial... | [
-0.03835572674870491,
-0.018993813544511795,
-0.031177829951047897,
-0.03226371854543686,
-0.010555186308920383,
-0.017963141202926636,
0.029742252081632614,
-0.0033427823800593615,
0.018469275906682014,
0.018340442329645157,
-0.0277545265853405,
0.025895636528730392,
-0.037048980593681335,
... | |||
wacv_2025_f358f97804 | f358f97804 | wacv | 2,025 | Towards Secure and Usable 3D Assets: A Novel Framework for Automatic Visible Watermarking | 3D models particularly AI-generated ones have witnessed a recent surge across various industries such as entertainment. Hence there is an alarming need to protect the intellectual property and avoid the misuse of these valuable assets. As a viable solution to address these concerns we rigorously define the novel task o... | Gursimran Singh; Tianxi Hu; Mohammad Akbari; Qiang Tang; Yong Zhang | Huawei Technologies Canada Co. Ltd.; Huawei Technologies Canada Co. Ltd.; Huawei Technologies Canada Co. Ltd.; Huawei Technologies Canada Co. Ltd.; Huawei Technologies Canada Co. Ltd. | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Singh_Towards_Secure_and_Usable_3D_Assets_A_Novel_Framework_for_WACV_2025_paper.html | 1 | 2409.00314 | Towards Secure and Usable 3D Assets: A Novel Framework for Automatic Visible Watermarking
3D models particularly AI-generated ones have witnessed a recent surge across various industries such as entertainment. Hence there is an alarming need to protect the intellectual property and avoid the misuse of these valuable as... | [
-0.022763609886169434,
0.0002519169938750565,
-0.022468458861112595,
-0.0016809838125482202,
-0.007517156656831503,
-0.008259648457169533,
-0.0014227256178855896,
0.015246453694999218,
0.0332968533039093,
0.025788920000195503,
0.0024788170121610165,
-0.0014261844335123897,
0.0232247859239578... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.