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wacv_2025_7e9da3e72f | 7e9da3e72f | wacv | 2,025 | Planar Gaussian Splatting | This paper presents Planar Gaussian Splatting (PGS) a novel neural rendering approach to learn the 3D geometry and parse the 3D planes of a scene directly from multiple RGB images. The PGS leverages Gaussian primitives to model the scene and employ a hierarchical Gaussian mixture approach to group them. Similar Gaussia... | Farhad G. Zanjani; Hong Cai; Hanno Ackermann; Leila Mirvakhabova; Fatih Porikli | Qualcomm AI Research*; Qualcomm AI Research*; Qualcomm AI Research*; Qualcomm AI Research*; Qualcomm AI Research* | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zanjani_Planar_Gaussian_Splatting_WACV_2025_paper.html | 1 | 2412.01931 | Planar Gaussian Splatting
This paper presents Planar Gaussian Splatting (PGS) a novel neural rendering approach to learn the 3D geometry and parse the 3D planes of a scene directly from multiple RGB images. The PGS leverages Gaussian primitives to model the scene and employ a hierarchical Gaussian mixture approach to g... | [
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wacv_2025_60fafbd26a | 60fafbd26a | wacv | 2,025 | PocoLoco: A Point Cloud Diffusion Model of Human Shape in Loose Clothing | Modeling a human avatar that can plausibly deform to articulations is an active area of research. We present PocoLoco - the first template-free point-based pose-conditioned generative model for 3D humans in loose clothing. We motivate our work by noting that most methods require a parametric model of the human body to ... | Siddharth Seth; Rishabh Dabral; Diogo C Luvizon; Marc Habermann; Ming-Hsuan Yang; Christian Theobalt; Adam Kortylewski | UC Merced; Max Planck Institute for Informatics; Max Planck Institute for Informatics; Max Planck Institute for Informatics; UC Merced; Max Planck Institute for Informatics; University of Freiburg+Max Planck Institute for Informatics | Poster | main | https://github.com/sidsunny/pocoloco | https://openaccess.thecvf.com/content/WACV2025/html/Seth_PocoLoco_A_Point_Cloud_Diffusion_Model_of_Human_Shape_in_WACV_2025_paper.html | 0 | 2411.04249 | PocoLoco: A Point Cloud Diffusion Model of Human Shape in Loose Clothing
Modeling a human avatar that can plausibly deform to articulations is an active area of research. We present PocoLoco - the first template-free point-based pose-conditioned generative model for 3D humans in loose clothing. We motivate our work by ... | [
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wacv_2025_91fc93cd19 | 91fc93cd19 | wacv | 2,025 | Point Cloud Color Upsampling with Attention-Based Coarse Colorization and Refinement | Point cloud color upsampling is an important and less explored research topic. State-of-the-art methods colorize points based on the colors of neighboring points and geometric distances. However these methods often suffer from blurring and noise at color boundaries since object textures can have large color variations ... | Kohei Matsuzaki; Keisuke Nonaka | KDDI Research, Inc.; KDDI Research, Inc. | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Matsuzaki_Point_Cloud_Color_Upsampling_with_Attention-Based_Coarse_Colorization_and_Refinement_WACV_2025_paper.html | 0 | Point Cloud Color Upsampling with Attention-Based Coarse Colorization and Refinement
Point cloud color upsampling is an important and less explored research topic. State-of-the-art methods colorize points based on the colors of neighboring points and geometric distances. However these methods often suffer from blurring... | [
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wacv_2025_ac5ac3e8a6 | ac5ac3e8a6 | wacv | 2,025 | Point-GN: A Non-Parametric Network using Gaussian Positional Encoding for Point Cloud Classification | This paper introduces Point-GN a novel non-parametric network for efficient and accurate 3D point cloud classification. Unlike conventional deep learning models that rely on a large number of trainable parameters Point-GN leverages non-learnable components-specifically Farthest Point Sampling (FPS) k-Nearest Neighbors ... | Marzieh Mohammadi; Amir Salarpour | Sirjan University of Technology, Iran; Sirjan University of Technology, Iran | Poster | main | https://github.com/asalarpour/Point_GN | https://openaccess.thecvf.com/content/WACV2025/html/Mohammadi_Point-GN_A_Non-Parametric_Network_using_Gaussian_Positional_Encoding_for_Point_WACV_2025_paper.html | 2 | Point-GN: A Non-Parametric Network using Gaussian Positional Encoding for Point Cloud Classification
This paper introduces Point-GN a novel non-parametric network for efficient and accurate 3D point cloud classification. Unlike conventional deep learning models that rely on a large number of trainable parameters Point-... | [
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wacv_2025_5d4fecb1fe | 5d4fecb1fe | wacv | 2,025 | Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud | Recent advancements in self-supervised learning in the point cloud domain have demonstrated significant potential. However these methods often suffer from drawbacks such as lengthy pre-training time the necessity of reconstruction in the input space and the necessity of additional modalities. In order to address these ... | Ayumu Saito; Prachi Kudeshia; Jiju Poovvancheri | Graphics and Spatial Computing Lab, Saint Mary’s University; Graphics and Spatial Computing Lab, Saint Mary’s University; Graphics and Spatial Computing Lab, Saint Mary’s University | Poster | main | https://github.com/Ayumu-J-S/Point-JEPA | https://openaccess.thecvf.com/content/WACV2025/html/Saito_Point-JEPA_A_Joint_Embedding_Predictive_Architecture_for_Self-Supervised_Learning_on_WACV_2025_paper.html | 6 | Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
Recent advancements in self-supervised learning in the point cloud domain have demonstrated significant potential. However these methods often suffer from drawbacks such as lengthy pre-training time the necessity of recons... | [
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wacv_2025_81a999a413 | 81a999a413 | wacv | 2,025 | Polarization as Texture: Microscale 3D Shape from Polarized Light Focus | Defocus is a crucial cue for image-based microscale depth estimation yet its measurement depends on spatial appearance changes such as texture. We show that passively observed polarization is responsive to small irregularities of the surface visible in the microscopic world and can be leveraged for focus measure as a s... | Ren Matsumoto; Takahiro Okabe; Ryo Kawahara | Kyushu Institute of Technology*; Okayama University†; Kyoto University‡ | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Matsumoto_Polarization_as_Texture_Microscale_3D_Shape_from_Polarized_Light_Focus_WACV_2025_paper.html | 0 | Polarization as Texture: Microscale 3D Shape from Polarized Light Focus
Defocus is a crucial cue for image-based microscale depth estimation yet its measurement depends on spatial appearance changes such as texture. We show that passively observed polarization is responsive to small irregularities of the surface visibl... | [
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wacv_2025_54a0079509 | 54a0079509 | wacv | 2,025 | PoolAtnRes: Towards Generalisable Differential Morphing Attack Detection | Morphing attacks can successfully deceive face recognition systems resulting in unreliable access control especially in the border control scenario. Consequently the development of Morphing Attack Detection (MAD) algorithms is crucial for detecting morphing attacks based on either a single facial image (S-MAD) or two f... | Raghavendra Ramachandra; Sushma Krupa Venkatesh; Guoqiang Li | Norwegian University of Science and Technology (NTNU), Norway; MOBAI AS, Norway; MOBAI AS, Norway | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ramachandra_PoolAtnRes_Towards_Generalisable_Differential_Morphing_Attack_Detection_WACV_2025_paper.html | 0 | PoolAtnRes: Towards Generalisable Differential Morphing Attack Detection
Morphing attacks can successfully deceive face recognition systems resulting in unreliable access control especially in the border control scenario. Consequently the development of Morphing Attack Detection (MAD) algorithms is crucial for detectin... | [
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wacv_2025_49390744bc | 49390744bc | wacv | 2,025 | PositiveCoOp: Rethinking Prompting Strategies for Multi-Label Recognition with Partial Annotations | Vision-language models (VLMs) like CLIP have been adapted for Multi-Label Recognition (MLR) with partial annotations by leveraging prompt-learning where positive and negative prompts are learned for each class to associate their embeddings with class presence or absence in the shared vision-text feature space. While th... | Samyak Rawlekar; Shubhang Bhatnagar; Narendra Ahuja | University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign; University of Illinois Urbana-Champaign | Poster | main | https://github.com/SamyakR99/PositiveCoOp | https://openaccess.thecvf.com/content/WACV2025/html/Rawlekar_PositiveCoOp_Rethinking_Prompting_Strategies_for_Multi-Label_Recognition_with_Partial_Annotations_WACV_2025_paper.html | 0 | PositiveCoOp: Rethinking Prompting Strategies for Multi-Label Recognition with Partial Annotations
Vision-language models (VLMs) like CLIP have been adapted for Multi-Label Recognition (MLR) with partial annotations by leveraging prompt-learning where positive and negative prompts are learned for each class to associat... | [
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wacv_2025_c3103e6061 | c3103e6061 | wacv | 2,025 | PostoMETRO: Pose Token Enhanced Mesh Transformer for Robust 3D Human Mesh Recovery | With the recent advancements in single-image-based 3D human pose and shape estimation (3DHPSE) there is a growing amount of works that can achieve good results on standard benchmarks but struggle to yield accurate human mesh in extreme scenarios like occlusion. Previous works propose to leverage 2D poses to help 3D HPS... | Wendi Yang; Zi-Hang Jiang; Shang Zhao; S. Kevin Zhou | ;;; | Poster | main | https://github.com/PostoMETRO/PostoMETRO-Paper | https://openaccess.thecvf.com/content/WACV2025/html/Yang_PostoMETRO_Pose_Token_Enhanced_Mesh_Transformer_for_Robust_3D_Human_WACV_2025_paper.html | 2 | 2403.12473 | PostoMETRO: Pose Token Enhanced Mesh Transformer for Robust 3D Human Mesh Recovery
With the recent advancements in single-image-based 3D human pose and shape estimation (3DHPSE) there is a growing amount of works that can achieve good results on standard benchmarks but struggle to yield accurate human mesh in extreme s... | [
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wacv_2025_6aafbd33bc | 6aafbd33bc | wacv | 2,025 | Pre-Capture Privacy via Adaptive Single-Pixel Imaging | As cameras become ubiquitous in our living environment invasion of privacy is becoming a significant concern. A common approach to privacy preservation is to remove personally identifiable information from a captured image but there is a risk of the original image being leaked. In this paper we propose a pre-capture pr... | Yoko Sogabe; Shiori Sugimoto; Ayumi Matsumoto; Masaki Kitahara | NTT Corporation, Japan; NTT Corporation, Japan; NTT Corporation, Japan; NTT Corporation, Japan | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Sogabe_Pre-Capture_Privacy_via_Adaptive_Single-Pixel_Imaging_WACV_2025_paper.html | 0 | 2407.00991 | Pre-Capture Privacy via Adaptive Single-Pixel Imaging
As cameras become ubiquitous in our living environment invasion of privacy is becoming a significant concern. A common approach to privacy preservation is to remove personally identifiable information from a captured image but there is a risk of the original image b... | [
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wacv_2025_71ffd4e444 | 71ffd4e444 | wacv | 2,025 | Pre-Trained Multiple Latent Variable Generative Models are Good Defenders Against Adversarial Attacks | Attackers can deliberately perturb classifiers' input with subtle noise altering final predictions. Among proposed countermeasures adversarial purification employs generative networks to preprocess input images filtering out adversarial noise. In this study we propose specific generators defined Multiple Latent Variabl... | Dario Serez; Marco Cristani; Alessio Del Bue; Vittorio Murino; Pietro Morerio | Istituto Italiano di Tecnologia, Italy+University of Genoa, Italy; University of Verona, Italy; Istituto Italiano di Tecnologia, Italy; Istituto Italiano di Tecnologia, Italy+University of Verona, Italy+University of Genoa, Italy; Istituto Italiano di Tecnologia, Italy | Poster | main | https://github.com/SerezD/gen_adversarial | https://openaccess.thecvf.com/content/WACV2025/html/Serez_Pre-Trained_Multiple_Latent_Variable_Generative_Models_are_Good_Defenders_Against_WACV_2025_paper.html | 0 | 2412.03453 | Pre-Trained Multiple Latent Variable Generative Models are Good Defenders Against Adversarial Attacks
Attackers can deliberately perturb classifiers' input with subtle noise altering final predictions. Among proposed countermeasures adversarial purification employs generative networks to preprocess input images filteri... | [
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wacv_2025_4a70621c97 | 4a70621c97 | wacv | 2,025 | Precise Integral in NeRFs: Overcoming the Approximation Errors of Numerical Quadrature | Neural Radiance Fields (NeRFs) use neural networks to translate spatial coordinates to corresponding volume density and directional radiance enabling realistic novel view synthesis through volume rendering. Rendering new viewpoints involves computing volume rendering integrals along rays usually approximated by numeric... | Boyuan Zhang; Zhenliang He; Meina Kan; Shiguang Shan | Key Lab of AI Safety, Institute of Computing Technology, CAS, China; Key Lab of AI Safety, Institute of Computing Technology, CAS, China; Key Lab of AI Safety, Institute of Computing Technology, CAS, China+University of Chinese Academy of Sciences, China; Key Lab of AI Safety, Institute of Computing Technology, CAS, Ch... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_Precise_Integral_in_NeRFs_Overcoming_the_Approximation_Errors_of_Numerical_WACV_2025_paper.html | 0 | Precise Integral in NeRFs: Overcoming the Approximation Errors of Numerical Quadrature
Neural Radiance Fields (NeRFs) use neural networks to translate spatial coordinates to corresponding volume density and directional radiance enabling realistic novel view synthesis through volume rendering. Rendering new viewpoints i... | [
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wacv_2025_3cee677dff | 3cee677dff | wacv | 2,025 | Predicting Event Memorability using Personalized Federated Learning | Lifelog images are very useful as memory cues for recalling past events. Estimating the level of event memory recall induced by a given lifelog image (event memorability) is useful for selecting images for cognitive interventions. Previous works for predicting event memorability follow a centralized model training para... | Sourasekhar Banerjee; Debaditya Roy; Vigneshwaran Subbaraju; Monowar Bhuyan | Uppsala University1+Ume ˚a University3; IHPC, A*STAR Singapore2; IHPC, A*STAR Singapore2; Ume ˚a University3 | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Banerjee_Predicting_Event_Memorability_using_Personalized_Federated_Learning_WACV_2025_paper.html | 1 | Predicting Event Memorability using Personalized Federated Learning
Lifelog images are very useful as memory cues for recalling past events. Estimating the level of event memory recall induced by a given lifelog image (event memorability) is useful for selecting images for cognitive interventions. Previous works for pr... | [
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wacv_2025_b78bf2fd84 | b78bf2fd84 | wacv | 2,025 | PrevPredMap: Exploring Temporal Modeling with Previous Predictions for Online Vectorized HD Map Construction | Temporal information is crucial for detecting occluded instances. Existing temporal representations have progressed from BEV or PV (perspective view) features to more compact query features. Compared to these aforementioned features predictions offer the highest level of abstraction providing explicit information. In t... | Nan Peng; Xun Zhou; Mingming Wang; Xiaojun Yang; Songming Chen; Guisong Chen | Ruqi Mobility; Ruqi Mobility; GAC R&D Center; Ruqi Mobility; GAC R&D Center; Ruqi Mobility | Poster | main | https://github.com/pnnnnnnn/PrevPredMap | https://openaccess.thecvf.com/content/WACV2025/html/Peng_PrevPredMap_Exploring_Temporal_Modeling_with_Previous_Predictions_for_Online_Vectorized_WACV_2025_paper.html | 5 | 2407.17378 | PrevPredMap: Exploring Temporal Modeling with Previous Predictions for Online Vectorized HD Map Construction
Temporal information is crucial for detecting occluded instances. Existing temporal representations have progressed from BEV or PV (perspective view) features to more compact query features. Compared to these af... | [
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wacv_2025_eb0064f706 | eb0064f706 | wacv | 2,025 | Prior2Posterior: Model Prior Correction for Long-Tailed Learning | Learning-based solutions for long-tailed recognition face difficulties in generalizing on balanced test datasets. Due to imbalanced data prior the learned a posteriori distribution is biased toward the most frequent (head) classes leading to an inferior performance on the least frequent (tail) classes. In general the p... | S Divakar Bhat; Amit More; Mudit Soni; Surbhi Agrawal | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Bhat_Prior2Posterior_Model_Prior_Correction_for_Long-Tailed_Learning_WACV_2025_paper.html | 1 | 2412.16540 | Prior2Posterior: Model Prior Correction for Long-Tailed Learning
Learning-based solutions for long-tailed recognition face difficulties in generalizing on balanced test datasets. Due to imbalanced data prior the learned a posteriori distribution is biased toward the most frequent (head) classes leading to an inferior p... | [
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wacv_2025_b4b6cdbdac | b4b6cdbdac | wacv | 2,025 | PrivateEye: In-Sensor Privacy Preservation Through Optical Feature Separation | We address privacy issues in applications where images captured by an edge device (camera) are sent to the cloud for inference on utility tasks such as classification. Sending raw images to the cloud exposes them to data sniffing attacks and misuse by untrusted third-party service providers beyond the user's intended t... | Adith Boloor; Weikai Lin; Tianrui Ma; Yu Feng; Yuhao Zhu; Xuan Zhang | Washington University in St. Louis; University of Rochester; Washington University in St. Louis; Shanghai Jiao Tong University; University of Rochester; Northeastern University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Boloor_PrivateEye_In-Sensor_Privacy_Preservation_Through_Optical_Feature_Separation_WACV_2025_paper.html | 0 | PrivateEye: In-Sensor Privacy Preservation Through Optical Feature Separation
We address privacy issues in applications where images captured by an edge device (camera) are sent to the cloud for inference on utility tasks such as classification. Sending raw images to the cloud exposes them to data sniffing attacks and ... | [
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wacv_2025_2a36e8446d | 2a36e8446d | wacv | 2,025 | Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge | This paper investigates how to efficiently deploy vision transformers on edge devices for small workloads. Recent methods reduce the latency of transformer neural networks by removing or merging tokens with small accuracy degradation. However these methods are not designed with edge device deployment in mind: they do n... | Nicholas John Eliopoulos; Purvish Jajal; James C. Davis; Gaowen Liu; George K. Thiruvathukal; Yung-Hsiang Lu | ;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Eliopoulos_Pruning_One_More_Token_is_Enough_Leveraging_Latency-Workload_Non-Linearities_for_WACV_2025_paper.html | 1 | 2407.05941 | Pruning One More Token is Enough: Leveraging Latency-Workload Non-Linearities for Vision Transformers on the Edge
This paper investigates how to efficiently deploy vision transformers on edge devices for small workloads. Recent methods reduce the latency of transformer neural networks by removing or merging tokens with... | [
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wacv_2025_51caaf3d77 | 51caaf3d77 | wacv | 2,025 | Psych-Occlusion: using Visual Psychophysics for Aerial Detection of Occluded Persons during Search and Rescue | The success of Emergency Response (ER) scenarios such as search and rescue is often dependent upon the prompt location of a lost or injured person. With the increasing use of small Unmanned Aerial Systems (sUAS) as "eyes in the sky" during ER scenarios efficient detection of persons from aerial views plays a crucial ro... | Arturo Miguel Russell Bernal; Jane Cleland-Huang; Walter Scheirer | Computer Science and Engineering Department, University of Notre Dame, Indiana, USA; Computer Science and Engineering Department, University of Notre Dame, Indiana, USA; Computer Science and Engineering Department, University of Notre Dame, Indiana, USA | Poster | main | https://github.com/ArtRuss/NOMAD | https://openaccess.thecvf.com/content/WACV2025/html/Bernal_Psych-Occlusion_using_Visual_Psychophysics_for_Aerial_Detection_of_Occluded_Persons_WACV_2025_paper.html | 0 | Psych-Occlusion: using Visual Psychophysics for Aerial Detection of Occluded Persons during Search and Rescue
The success of Emergency Response (ER) scenarios such as search and rescue is often dependent upon the prompt location of a lost or injured person. With the increasing use of small Unmanned Aerial Systems (sUAS... | [
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wacv_2025_b5242d2395 | b5242d2395 | wacv | 2,025 | PureForest: A Large-Scale Aerial Lidar and Aerial Imagery Dataset for Tree Species Classification in Monospecific Forests | Sustainable forest management is a cornerstone of climate and environmental action. Responsible management relies on forest models such as biomass or fire vulnerability estimates which depend on mapping the spatial distribution of tree species. Because forest mapping relies heavily on visual identification it is a time... | Charles Gaydon; Floryne Roche | ; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Gaydon_PureForest_A_Large-Scale_Aerial_Lidar_and_Aerial_Imagery_Dataset_for_WACV_2025_paper.html | 3 | 2404.12064 | PureForest: A Large-Scale Aerial Lidar and Aerial Imagery Dataset for Tree Species Classification in Monospecific Forests
Sustainable forest management is a cornerstone of climate and environmental action. Responsible management relies on forest models such as biomass or fire vulnerability estimates which depend on map... | [
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wacv_2025_a8c517f346 | a8c517f346 | wacv | 2,025 | Q-TempFusion: Quantization-Aware Temporal Multi-Sensor Fusion on Bird's-Eye View Representation | Recent advancements in bird's-eye view (BEV) perception models have highlighted the superior performance of LiDAR-camera fusion systems over single-modality approaches garnering considerable interest in the field. Despite the progress the integration of temporal information a technique that has considerably benefitted ... | Pinrui Yu; Zhenglun Kong; Pu Zhao; Peiyan Dong; Hao Tang; Fei Sun; Xue Lin; Yanzhi Wang | Northeastern University; Northeastern University; Northeastern University; Northeastern University; CVL, ETH Zurich; Meta Inc.; Northeastern University; Northeastern University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yu_Q-TempFusion_Quantization-Aware_Temporal_Multi-Sensor_Fusion_on_Birds-Eye_View_Representation_WACV_2025_paper.html | 0 | Q-TempFusion: Quantization-Aware Temporal Multi-Sensor Fusion on Bird's-Eye View Representation
Recent advancements in bird's-eye view (BEV) perception models have highlighted the superior performance of LiDAR-camera fusion systems over single-modality approaches garnering considerable interest in the field. Despite th... | [
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wacv_2025_ef0e8583e3 | ef0e8583e3 | wacv | 2,025 | QuantAttack: Exploiting Quantization Techniques to Attack Vision Transformers | In recent years there has been a significant trend in deep neural networks (DNNs) particularly transformer-based models of developing ever-larger and more capable models. While they demonstrate state-of-the-art performance their growing scale requires increased computational resources (e.g. GPUs with greater memory cap... | Amit Baras; Alon Zolfi; Yuval Elovici; Asaf Shabtai | Ben-Gurion University of the Negev, Israel; Ben-Gurion University of the Negev, Israel; Ben-Gurion University of the Negev, Israel; Ben-Gurion University of the Negev, Israel | Poster | main | https://github.com/barasamit/QuantAttack | https://openaccess.thecvf.com/content/WACV2025/html/Baras_QuantAttack_Exploiting_Quantization_Techniques_to_Attack_Vision_Transformers_WACV_2025_paper.html | 0 | QuantAttack: Exploiting Quantization Techniques to Attack Vision Transformers
In recent years there has been a significant trend in deep neural networks (DNNs) particularly transformer-based models of developing ever-larger and more capable models. While they demonstrate state-of-the-art performance their growing scale... | [
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wacv_2025_1a5de5c96f | 1a5de5c96f | wacv | 2,025 | RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation | Current deep learning approaches in computer vision primarily focus on RGB data sacrificing information. In contrast RAW images offer richer representation which is crucial for precise recognition particularly in challenging conditions like low-light environments. The resultant demand for comprehensive RAW image datase... | Christoph Reinders; Radu Berdan; Beril Besbinar; Junji Otsuka; Daisuke Iso | Leibniz University Hannover; Sony AI; Sony AI; Sony Group Corporation; Sony AI | Poster | main | https://github.com/SonyResearch/RAW-Diffusion | https://openaccess.thecvf.com/content/WACV2025/html/Reinders_RAW-Diffusion_RGB-Guided_Diffusion_Models_for_High-Fidelity_RAW_Image_Generation_WACV_2025_paper.html | 3 | RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation
Current deep learning approaches in computer vision primarily focus on RGB data sacrificing information. In contrast RAW images offer richer representation which is crucial for precise recognition particularly in challenging conditions li... | [
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wacv_2025_3c0748a8db | 3c0748a8db | wacv | 2,025 | RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples | Selecting representative samples plays an indispensable role in many machine learning and computer vision applications under limited resources (e.g. limited communication bandwidth and computational power). Determinantal Point Process (DPP) is a widely used method for selecting the most diverse representative samples t... | Xiwen Chen; Huayu Li; Peijie Qiu; Wenhui Zhu; Rahul Amin; Abolfazl Razi | Clemson University; University of Arizona; Washington University in St. Louis; Arizona State University; MIT Lincoln Laboratory; Clemson University | Poster | main | https://github.com/xiwenc1/RD-DPP1 | https://openaccess.thecvf.com/content/WACV2025/html/Chen_RD-DPP_Rate-Distortion_Theory_Meets_Determinantal_Point_Process_to_Diversify_Learning_WACV_2025_paper.html | 5 | RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples
Selecting representative samples plays an indispensable role in many machine learning and computer vision applications under limited resources (e.g. limited communication bandwidth and computational power). Determinantal... | [
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wacv_2025_e50bce3538 | e50bce3538 | wacv | 2,025 | RGB-D Video Mirror Detection | Mirror detection aims to identify mirror areas in a scene with recent methods either integrating depth information (RGB-D) or making use of temporal information (video). However utilizing both data is still under-explored due to the lack of a high-quality dataset and an effective method for the RGB-D Video Mirror Detec... | Mingchen Xu; Peter Herbert; Yu-Kun Lai; Ze Ji; Jing Wu | School of Computer Science and Informatics, Cardiff University; School of Computer Science and Informatics, Cardiff University; School of Computer Science and Informatics, Cardiff University; School of Engineering, Cardiff University; School of Computer Science and Informatics, Cardiff University | Poster | main | https://github.com/UpChen/2025_DVMDNet | https://openaccess.thecvf.com/content/WACV2025/html/Xu_RGB-D_Video_Mirror_Detection_WACV_2025_paper.html | 0 | RGB-D Video Mirror Detection
Mirror detection aims to identify mirror areas in a scene with recent methods either integrating depth information (RGB-D) or making use of temporal information (video). However utilizing both data is still under-explored due to the lack of a high-quality dataset and an effective method for... | [
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wacv_2025_fb8d7b53ef | fb8d7b53ef | wacv | 2,025 | RGB2Point: 3D Point Cloud Generation from Single RGB Images | We introduce RGB2Point an unposed single-view RGB image to a 3D point cloud generation based on Transformer. RGB2Point takes an input image of an object and generates a dense 3D point cloud. Contrary to prior works based on CNN layers and diffusion-denoising approaches we use pre-trained Transformer layers that are fas... | Jae Joong Lee; Bedrich Benes | Department of Computer Science, Purdue University, West Lafayette, USA; Department of Computer Science, Purdue University, West Lafayette, USA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lee_RGB2Point_3D_Point_Cloud_Generation_from_Single_RGB_Images_WACV_2025_paper.html | 1 | 2407.14979 | RGB2Point: 3D Point Cloud Generation from Single RGB Images
We introduce RGB2Point an unposed single-view RGB image to a 3D point cloud generation based on Transformer. RGB2Point takes an input image of an object and generates a dense 3D point cloud. Contrary to prior works based on CNN layers and diffusion-denoising a... | [
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wacv_2025_455e08731e | 455e08731e | wacv | 2,025 | ROADS: Robust Prompt-Driven Multi-Class Anomaly Detection under Domain Shift | Recent advancements in anomaly detection have shifted focus towards Multi-class Unified Anomaly Detection (MUAD) offering more scalable and practical alternatives compared to traditional one-class-one-model approaches. However existing MUAD methods often suffer from inter-class interference and are highly susceptible t... | Hossein Kashiani; Niloufar Alipour Talemi; Fatemeh Afghah | Clemson University; Clemson University; Clemson University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kashiani_ROADS_Robust_Prompt-Driven_Multi-Class_Anomaly_Detection_under_Domain_Shift_WACV_2025_paper.html | 2 | 2411.16049 | ROADS: Robust Prompt-Driven Multi-Class Anomaly Detection under Domain Shift
Recent advancements in anomaly detection have shifted focus towards Multi-class Unified Anomaly Detection (MUAD) offering more scalable and practical alternatives compared to traditional one-class-one-model approaches. However existing MUAD me... | [
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wacv_2025_d272e45fa2 | d272e45fa2 | wacv | 2,025 | ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfer | Reconstructing an object's shape and appearance in terms of a mesh textured by a spatially-varying bidirectional reflectance distribution function (SVBRDF) from a limited set of images captured under collocated light is an ill-posed problem. Previous state-of-the-art approaches either aim to reconstruct the appearance ... | Julian Kaltheuner; Patrick Stotko; Reinhard Klein | University of Bonn; University of Bonn; University of Bonn | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kaltheuner_ROSA_Reconstructing_Object_Shape_and_Appearance_Textures_by_Adaptive_Detail_WACV_2025_paper.html | 0 | 2501.18595 | ROSA: Reconstructing Object Shape and Appearance Textures by Adaptive Detail Transfer
Reconstructing an object's shape and appearance in terms of a mesh textured by a spatially-varying bidirectional reflectance distribution function (SVBRDF) from a limited set of images captured under collocated light is an ill-posed p... | [
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wacv_2025_0d0e613c4e | 0d0e613c4e | wacv | 2,025 | RT-DETRv3: Real-Time End-to-End Object Detection with Hierarchical Dense Positive Supervision | RT-DETR is the first real-time end-to-end transformer-based object detector. Its efficiency comes from the framework design and the Hungarian matching. However compared to dense supervision detectors like the YOLO series the Hungarian matching provides much sparser supervision leading to insufficient model training and... | Shuo Wang; Chunlong Xia; Feng Lv; Yifeng Shi | Baidu Inc, China; Baidu Inc, China; Baidu Inc, China; Baidu Inc, China | Poster | main | https://github.com/clxia12/RT-DETRv3 | https://openaccess.thecvf.com/content/WACV2025/html/Wang_RT-DETRv3_Real-Time_End-to-End_Object_Detection_with_Hierarchical_Dense_Positive_Supervision_WACV_2025_paper.html | 13 | RT-DETRv3: Real-Time End-to-End Object Detection with Hierarchical Dense Positive Supervision
RT-DETR is the first real-time end-to-end transformer-based object detector. Its efficiency comes from the framework design and the Hungarian matching. However compared to dense supervision detectors like the YOLO series the H... | [
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wacv_2025_e13a118580 | e13a118580 | wacv | 2,025 | Radiance Field-Based Pose Estimation via Decoupled Optimization Under Challenging Initial Conditions | Estimating six-degree-of-freedom poses is essential but difficult especially under challenging initial conditions as existing methods relying on photometric loss often fail catastrophically. To address this we propose a novel radiance field-based pose estimation framework that combines Monte Carlo initialization and de... | Si-Yu Lu; Yung-Yao Chen; Yi-Tong Wu; Hsin-Chun Lin; Sin-Ye Jhong; Wen-Huang Cheng | National Taiwan University; National Taiwan University of Science and Technology; National Taiwan University of Science and Technology; National Taiwan University of Science and Technology; National Taiwan University of Science and Technology; National Taiwan University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lu_Radiance_Field-Based_Pose_Estimation_via_Decoupled_Optimization_Under_Challenging_Initial_WACV_2025_paper.html | 0 | Radiance Field-Based Pose Estimation via Decoupled Optimization Under Challenging Initial Conditions
Estimating six-degree-of-freedom poses is essential but difficult especially under challenging initial conditions as existing methods relying on photometric loss often fail catastrophically. To address this we propose a... | [
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wacv_2025_147053ed58 | 147053ed58 | wacv | 2,025 | RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone | Vision transformers (ViTs) have dominated computer vision in recent years. However ViTs are computationally expensive and not well suited for mobile devices; this led to the prevalence of convolutional neural network (CNN) and ViT-based hybrid models for mobile vision applications. Recently Vision GNN (ViG) and CNN hyb... | Mustafa Munir; Md Mostafijur Rahman; Radu Marculescu | The University of Texas at Austin; The University of Texas at Austin; The University of Texas at Austin | Poster | main | https://github.com/mmunir127/RapidNet-Official | https://openaccess.thecvf.com/content/WACV2025/html/Munir_RapidNet_Multi-Level_Dilated_Convolution_Based_Mobile_Backbone_WACV_2025_paper.html | 0 | 2412.10995 | RapidNet: Multi-Level Dilated Convolution Based Mobile Backbone
Vision transformers (ViTs) have dominated computer vision in recent years. However ViTs are computationally expensive and not well suited for mobile devices; this led to the prevalence of convolutional neural network (CNN) and ViT-based hybrid models for m... | [
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wacv_2025_e983ae53b9 | e983ae53b9 | wacv | 2,025 | RayGauss: Volumetric Gaussian-Based Ray Casting for Photorealistic Novel View Synthesis | Differentiable volumetric rendering-based methods made significant progress in novel view synthesis. On one hand innovative methods have replaced the Neural Radiance Fields (NeRF) network with locally parameterized structures enabling high-quality renderings in a reasonable time. On the other hand approaches have used ... | Hugo Blanc; Jean-Emmanuel Deschaud; Alexis Paljic | Centre for Robotics, Mines Paris - PSL, PSL University, 75006 Paris, France; Centre for Robotics, Mines Paris - PSL, PSL University, 75006 Paris, France; Centre for Robotics, Mines Paris - PSL, PSL University, 75006 Paris, France | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Blanc_RayGauss_Volumetric_Gaussian-Based_Ray_Casting_for_Photorealistic_Novel_View_Synthesis_WACV_2025_paper.html | 4 | 2408.03356 | RayGauss: Volumetric Gaussian-Based Ray Casting for Photorealistic Novel View Synthesis
Differentiable volumetric rendering-based methods made significant progress in novel view synthesis. On one hand innovative methods have replaced the Neural Radiance Fields (NeRF) network with locally parameterized structures enabli... | [
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wacv_2025_c1df12f77b | c1df12f77b | wacv | 2,025 | Re-Evaluating Group Robustness via Adaptive Class-Specific Scaling | Group distributionally robust optimization which aims to improve robust accuracies--worst-group and unbiased accuracies--is a prominent algorithm used to mitigate spurious correlations and address dataset bias. Although existing approaches have reported improvements in robust accuracies these gains often come at the co... | Seonguk Seo; Bohyung Han | ECE; ECE + IPAI | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Seo_Re-Evaluating_Group_Robustness_via_Adaptive_Class-Specific_Scaling_WACV_2025_paper.html | 0 | 2412.15311 | Re-Evaluating Group Robustness via Adaptive Class-Specific Scaling
Group distributionally robust optimization which aims to improve robust accuracies--worst-group and unbiased accuracies--is a prominent algorithm used to mitigate spurious correlations and address dataset bias. Although existing approaches have reported... | [
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wacv_2025_2032f78b5e | 2032f78b5e | wacv | 2,025 | Re-Identifying People in Video via Learned Temporal Attention and Multi-Modal Foundation Models | Biometric recognition from security camera video is a challenging problem when the individuals change clothes or when they are partly occluded. Others have recently demonstrated that CLIP's visual encoder performs well in this domain but existing methods fail to make use of the model's text encoder or temporal informat... | Cole Hill; Florence Yellin; Krishna Regmi; Dawei Du; Scott McCloskey | Kitware Inc., USA+University of South Florida, USA; Kitware Inc., USA; Kitware Inc., USA; Kitware Inc., USA; Kitware Inc., USA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Hill_Re-Identifying_People_in_Video_via_Learned_Temporal_Attention_and_Multi-Modal_WACV_2025_paper.html | 0 | Re-Identifying People in Video via Learned Temporal Attention and Multi-Modal Foundation Models
Biometric recognition from security camera video is a challenging problem when the individuals change clothes or when they are partly occluded. Others have recently demonstrated that CLIP's visual encoder performs well in th... | [
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wacv_2025_594ff86fde | 594ff86fde | wacv | 2,025 | ReBotNet: Fast Real-Time Video Enhancement | Most video restoration networks are slow have high computational load and can't be used for real-time video enhancement. In this work we design an efficient and fast framework to perform real-time video enhancement for practical use-cases like live video calls and video streams. Our proposed method called Recurrent Bot... | Jeya Maria Jose Valanarasu; Rahul Garg; Andeep Toor; Xin Tong; Weijuan Xi; Andreas Lugmayr; Vishal M. Patel; Anne Menini | Google; Google; Google; Google; Google; ETH Zurich; Johns Hopkins University; Google | Poster | main | https://github.com/jeya-maria-jose/rebot-net | https://openaccess.thecvf.com/content/WACV2025/html/Valanarasu_ReBotNet_Fast_Real-Time_Video_Enhancement_WACV_2025_paper.html | 1 | 2303.13504 | ReBotNet: Fast Real-Time Video Enhancement
Most video restoration networks are slow have high computational load and can't be used for real-time video enhancement. In this work we design an efficient and fast framework to perform real-time video enhancement for practical use-cases like live video calls and video stream... | [
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wacv_2025_58f5a08c9c | 58f5a08c9c | wacv | 2,025 | ReC-TTT: Contrastive Feature Reconstruction for Test-Time Training | The remarkable progress in deep learning (DL) showcases outstanding results in various computer vision tasks. However adaptation to real-time variations in data distributions remains an important challenge. Test-Time Training (TTT) was proposed as an effective solution to this issue which increases the generalization a... | Marco Colussi; Sergio Mascetti; Jose Dolz; Christian Desrosiers | Universit `a degli studi di Milano; Universit `a degli studi di Milano; ´ETS Montr ´eal; ´ETS Montr ´eal | Poster | main | https://github.com/warpcut/ReC-TTT | https://openaccess.thecvf.com/content/WACV2025/html/Colussi_ReC-TTT_Contrastive_Feature_Reconstruction_for_Test-Time_Training_WACV_2025_paper.html | 0 | ReC-TTT: Contrastive Feature Reconstruction for Test-Time Training
The remarkable progress in deep learning (DL) showcases outstanding results in various computer vision tasks. However adaptation to real-time variations in data distributions remains an important challenge. Test-Time Training (TTT) was proposed as an ef... | [
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wacv_2025_cdc6889db3 | cdc6889db3 | wacv | 2,025 | ReEdit: Multimodal Exemplar-Based Image Editing | Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic images. While the de-facto method for performing edits with T2I models is through text instructions this approach is non-trivial due to the complex many-to-many mapping between natural... | Ashutosh Srivastava; Tarun Ram Menta; Abhinav Java; Avadhoot Gorakh Jadhav; Silky Singh; Surgan Jandial; Balaji Krishnamurthy | Indian Institute of Technology, Roorkee; Adobe MDSR; Microsoft Research; Indian Institute of Technology, Bombay; Stanford University; Carnegie Mellon University; Adobe MDSR | Poster | main | https://reedit-diffusion.github.io/ | https://openaccess.thecvf.com/content/WACV2025/html/Srivastava_ReEdit_Multimodal_Exemplar-Based_Image_Editing_WACV_2025_paper.html | 0 | 2411.03982 | ReEdit: Multimodal Exemplar-Based Image Editing
Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic images. While the de-facto method for performing edits with T2I models is through text instructions this approach is non-trivial due to ... | [
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wacv_2025_d32b6678b4 | d32b6678b4 | wacv | 2,025 | ReFu: Recursive Fusion for Exemplar-Free 3D Class-Incremental Learning | We introduce a novel Recursive Fusion model dubbed ReFu designed to integrate point clouds and meshes for exemplar-free 3D Class-Incremental Learning where the model learns new 3D classes while retaining knowledge of previously learned ones. Unlike existing methods that either rely on storing historical data to mitigat... | Yi Yang; Lei Zhong; Huiping Zhuang | The University of Edinburgh; The University of Edinburgh; South China University of Technology | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yang_ReFu_Recursive_Fusion_for_Exemplar-Free_3D_Class-Incremental_Learning_WACV_2025_paper.html | 0 | 2409.12326 | ReFu: Recursive Fusion for Exemplar-Free 3D Class-Incremental Learning
We introduce a novel Recursive Fusion model dubbed ReFu designed to integrate point clouds and meshes for exemplar-free 3D Class-Incremental Learning where the model learns new 3D classes while retaining knowledge of previously learned ones. Unlike ... | [
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wacv_2025_06ecd55a0e | 06ecd55a0e | wacv | 2,025 | ReMP: Reusable Motion Prior for Multi-Domain 3D Human Pose Estimation and Motion Inbetweening | We present Reusable Motion prior (ReMP) an effective motion prior that can accurately track the temporal evolution of motion in various downstream tasks. Inspired by the success of foundation models we argue that a robust spatio-temporal motion prior can encapsulate underlying 3D dynamics applicable to various sensor m... | Hojun Jang; Young Min Kim | Dept. of Electrical and Computer Engineering, Seoul National University + Interdisciplinary Program in Artificial Intelligence and INMC, Seoul National University; Dept. of Electrical and Computer Engineering, Seoul National University + Interdisciplinary Program in Artificial Intelligence and INMC, Seoul National Univ... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Jang_ReMP_Reusable_Motion_Prior_for_Multi-Domain_3D_Human_Pose_Estimation_WACV_2025_paper.html | 0 | 2411.09435 | ReMP: Reusable Motion Prior for Multi-Domain 3D Human Pose Estimation and Motion Inbetweening
We present Reusable Motion prior (ReMP) an effective motion prior that can accurately track the temporal evolution of motion in various downstream tasks. Inspired by the success of foundation models we argue that a robust spat... | [
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wacv_2025_cb7eabf460 | cb7eabf460 | wacv | 2,025 | ReMix: Training Generalized Person Re-Identification on a Mixture of Data | Modern person re-identification (Re-ID) methods have a weak generalization ability and experience a major accuracy drop when capturing environments change. This is because existing multi-camera Re-ID datasets are limited in size and diversity since such data is difficult to obtain. At the same time enormous volumes of ... | Timur Mamedov; Anton Konushin; Vadim Konushin | Tevian, Moscow, Russia+Lomonosov Moscow State University; AIRI, Moscow, Russia+Lomonosov Moscow State University; Tevian, Moscow, Russia | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Mamedov_ReMix_Training_Generalized_Person_Re-Identification_on_a_Mixture_of_Data_WACV_2025_paper.html | 3 | 2410.21938 | ReMix: Training Generalized Person Re-Identification on a Mixture of Data
Modern person re-identification (Re-ID) methods have a weak generalization ability and experience a major accuracy drop when capturing environments change. This is because existing multi-camera Re-ID datasets are limited in size and diversity sin... | [
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wacv_2025_af25ee3841 | af25ee3841 | wacv | 2,025 | Realistic and Efficient Face Swapping: A Unified Approach with Diffusion Models | Despite promising progress in face swapping task realistic swapped images remain elusive often marred by artifacts particularly in scenarios involving high pose variation color differences and occlusion. To address these issues we propose a novel approach that better harnesses diffusion models for face-swapping by maki... | Sanoojan Baliah; Qinliang Lin; Shengcai Liao; Xiaodan Liang; Muhammad Haris Khan | MBZUAI, UAE; Shenzhen University, China; United Arab Emirates University, UAE; MBZUAI, UAE; MBZUAI, UAE | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Baliah_Realistic_and_Efficient_Face_Swapping_A_Unified_Approach_with_Diffusion_WACV_2025_paper.html | 5 | 2409.07269 | Realistic and Efficient Face Swapping: A Unified Approach with Diffusion Models
Despite promising progress in face swapping task realistic swapped images remain elusive often marred by artifacts particularly in scenarios involving high pose variation color differences and occlusion. To address these issues we propose a... | [
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wacv_2025_9720c5b894 | 9720c5b894 | wacv | 2,025 | Recognizing Unseen States of Unknown Objects by Leveraging Knowledge Graphs | We investigate the problem of Object State Classification (OSC) in the context of zero-shot learning. Specifically we propose the first method for Zero-shot Object-agnostic State Classification (OaSC) that given an image infers the state of a single object without relying on the knowledge or the estimation of the objec... | Filippos Gouidis; Konstantinos Papoutsakis; Theodore Patkos; Antonis Argyros; Dimitris Plexousakis | Foundation for Research and Technology-Hellas, Greece + University of Crete, Greece; Hellenic Mediterranean University, Greece; Foundation for Research and Technology-Hellas, Greece; Foundation for Research and Technology-Hellas, Greece + University of Crete, Greece; Foundation for Research and Technology-Hellas, Greec... | Poster | main | https://github.com/philipposg/OaSC.git | https://openaccess.thecvf.com/content/WACV2025/html/Gouidis_Recognizing_Unseen_States_of_Unknown_Objects_by_Leveraging_Knowledge_Graphs_WACV_2025_paper.html | 0 | Recognizing Unseen States of Unknown Objects by Leveraging Knowledge Graphs
We investigate the problem of Object State Classification (OSC) in the context of zero-shot learning. Specifically we propose the first method for Zero-shot Object-agnostic State Classification (OaSC) that given an image infers the state of a s... | [
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wacv_2025_10106a0e44 | 10106a0e44 | wacv | 2,025 | Recoverable Anonymization for Pose Estimation: A Privacy-Enhancing Approach | Human pose estimation (HPE) is crucial for various applications. However deploying HPE algorithms in surveillance contexts raises significant privacy concerns due to the potential leakage of sensitive personal information (SPI) such as facial features and ethnicity. Existing privacy-enhancing methods often compromise e... | Wenjun Huang; Yang Ni; Arghavan Rezvani Dehaghani; SungHeon Evan Jeong; Hanning Chen; Yezi Liu; Fei Wen; Mohsen Imani | University of California, Irvine, USA; University of California, Irvine, USA; University of California, Irvine, USA; University of California, Irvine, USA; University of California, Irvine, USA; University of California, Irvine, USA; Texas A&M University, USA; University of California, Irvine, USA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Huang_Recoverable_Anonymization_for_Pose_Estimation_A_Privacy-Enhancing_Approach_WACV_2025_paper.html | 3 | Recoverable Anonymization for Pose Estimation: A Privacy-Enhancing Approach
Human pose estimation (HPE) is crucial for various applications. However deploying HPE algorithms in surveillance contexts raises significant privacy concerns due to the potential leakage of sensitive personal information (SPI) such as facial f... | [
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wacv_2025_35fb5d7181 | 35fb5d7181 | wacv | 2,025 | Recurrence-Based Vanishing Point Detection | Classical approaches to Vanishing Point Detection (VPD) rely solely on the presence of explicit straight lines in images. Recent supervised deep learning methods rely on learned filters from labeled datasets. We propose an alternative unsupervised approach: Recurrence-based Vanishing Point Detection (R-VPD) that uses i... | Skanda Bharadwaj; Robert T. Collins; Yanxi Liu | School of EECS, The Pennsylvania State University, University Park, PA; School of EECS, The Pennsylvania State University, University Park, PA; School of EECS, The Pennsylvania State University, University Park, PA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Bharadwaj_Recurrence-Based_Vanishing_Point_Detection_WACV_2025_paper.html | 0 | 2412.20666 | Recurrence-Based Vanishing Point Detection
Classical approaches to Vanishing Point Detection (VPD) rely solely on the presence of explicit straight lines in images. Recent supervised deep learning methods rely on learned filters from labeled datasets. We propose an alternative unsupervised approach: Recurrence-based Va... | [
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wacv_2025_d2466691c2 | d2466691c2 | wacv | 2,025 | Reducing the Content Bias for AI-Generated Image Detection | Identifying AI-generated content is critical for the safe and ethical use of generative AI. Recent research has focused on developing detectors that generalize to unknown generators with popular methods relying either on high-level features or low-level fingerprints. However these methods have clear limitations: biased... | Seoyeon Gye; Junwon Ko; Hyounguk Shon; Minchan Kwon; Junmo Kim | School of Electrical Engineering, KAIST, South Korea; School of Electrical Engineering, KAIST, South Korea; School of Electrical Engineering, KAIST, South Korea; School of Electrical Engineering, KAIST, South Korea; School of Electrical Engineering, KAIST, South Korea | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Gye_Reducing_the_Content_Bias_for_AI-Generated_Image_Detection_WACV_2025_paper.html | 0 | Reducing the Content Bias for AI-Generated Image Detection
Identifying AI-generated content is critical for the safe and ethical use of generative AI. Recent research has focused on developing detectors that generalize to unknown generators with popular methods relying either on high-level features or low-level fingerp... | [
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wacv_2025_857efb304c | 857efb304c | wacv | 2,025 | RefVSR++: Exploiting Reference Inputs for Reference-Based Video Super-Resolution | Smartphones with multi-camera systems featuring cameras with varying field-of-views (FoVs) are increasingly common. This variation in FoVs results in content differences across videos paving the way for an innovative approach to video super-resolution (VSR). This method enhances the VSR performance of lower resolution ... | Han Zou; Masanori Suganuma; Takayuki Okatani | Graduate School of Information Sciences, Tohoku University+RIKEN Center for AIP; Graduate School of Information Sciences, Tohoku University+RIKEN Center for AIP; Graduate School of Information Sciences, Tohoku University+RIKEN Center for AIP | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zou_RefVSR_Exploiting_Reference_Inputs_for_Reference-Based_Video_Super-Resolution_WACV_2025_paper.html | 0 | RefVSR++: Exploiting Reference Inputs for Reference-Based Video Super-Resolution
Smartphones with multi-camera systems featuring cameras with varying field-of-views (FoVs) are increasingly common. This variation in FoVs results in content differences across videos paving the way for an innovative approach to video supe... | [
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wacv_2025_7061d1afa5 | 7061d1afa5 | wacv | 2,025 | Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation | Over the past few years Text-to-Image (T2I) generation approaches based on diffusion models have gained significant attention. However vanilla diffusion models often suffer from spelling inaccuracies in the text displayed within the generated images. The capability to generate visual text is crucial offering both acade... | Sanyam Lakhanpal; Shivang Chopra; Vinija Jain; Aman Chadha; Man Luo | Arizona State University; Georgia Institute of Technology; Meta AI; Amazon GenAI; Intel Lab | Poster | main | https://github.com/SanyamLakhanpal/SAOcr/tree/main | https://openaccess.thecvf.com/content/WACV2025/html/Lakhanpal_Refining_Text-to-Image_Generation_Towards_Accurate_Training-Free_Glyph-Enhanced_Image_Generation_WACV_2025_paper.html | 9 | 2403.16422 | Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation
Over the past few years Text-to-Image (T2I) generation approaches based on diffusion models have gained significant attention. However vanilla diffusion models often suffer from spelling inaccuracies in the text displayed ... | [
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wacv_2025_9ef5bc9f8d | 9ef5bc9f8d | wacv | 2,025 | Reflective Teacher: Semi-Supervised Multimodal 3D Object Detection in Bird's-Eye-View via Uncertainty Measure | Applying pseudo labeling techniques has been found to be advantageous in semi-supervised 3D object detection (SSOD) in Bird's-Eye-View (BEV) for autonomous driving particularly where labeled data is limited. In the literature Exponential Moving Average (EMA) has been used for adjustments of the weights of teacher netwo... | Saheli Hazra; Sudip Das; Rohit Choudhary; Arindam Das; Ganesh Sistu; Ciarán Eising; Ujjwal Bhattacharya | ;;;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Hazra_Reflective_Teacher_Semi-Supervised_Multimodal_3D_Object_Detection_in_Birds-Eye-View_via_WACV_2025_paper.html | 0 | Reflective Teacher: Semi-Supervised Multimodal 3D Object Detection in Bird's-Eye-View via Uncertainty Measure
Applying pseudo labeling techniques has been found to be advantageous in semi-supervised 3D object detection (SSOD) in Bird's-Eye-View (BEV) for autonomous driving particularly where labeled data is limited. In... | [
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wacv_2025_26ba90ced2 | 26ba90ced2 | wacv | 2,025 | Reframing Image Difference Captioning with BLIP2IDC and Synthetic Augmentation | The rise of the generative models quality during the past years enabled the generation of edited variations of images at an important scale. To counter the harmful effects of such technology the Image Difference Captioning (IDC) task aims to describe the differences between two images. While this task is successfully h... | Gautier Evennou; Antoine Chaffin; Vivien Chappelier; Ewa Kijak | IMATAG, France+IRISA, CNRS, France; LightOn, France+IMATAG, France+IRISA, CNRS, France; IMATAG, France; IRISA, CNRS, France | Poster | main | https://github.com/gautierevn/BLIP2IDC | https://openaccess.thecvf.com/content/WACV2025/html/Evennou_Reframing_Image_Difference_Captioning_with_BLIP2IDC_and_Synthetic_Augmentation_WACV_2025_paper.html | 0 | 2412.15939 | Reframing Image Difference Captioning with BLIP2IDC and Synthetic Augmentation
The rise of the generative models quality during the past years enabled the generation of edited variations of images at an important scale. To counter the harmful effects of such technology the Image Difference Captioning (IDC) task aims to... | [
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wacv_2025_747c5a7a70 | 747c5a7a70 | wacv | 2,025 | ReinDiffuse: Crafting Physically Plausible Motions with Reinforced Diffusion Model | Generating human motion from textual descriptions is a challenging task. Existing methods either struggle with physical credibility or are limited by the complexities of physics simulations. In this paper we present ReinDiffuse that combines reinforcement learning with motion diffusion model to generate physically cred... | Gaoge Han; Mingjiang Liang; Jinglei Tang; Yongkang Cheng; Wei Liu; Shaoli Huang | Northwest A&F University; University of Technology Sydney; Northwest A&F University + Tencent AI Lab; Tencent AI Lab; University of Technology Sydney; Tencent AI Lab | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Han_ReinDiffuse_Crafting_Physically_Plausible_Motions_with_Reinforced_Diffusion_Model_WACV_2025_paper.html | 7 | 2410.07296 | ReinDiffuse: Crafting Physically Plausible Motions with Reinforced Diffusion Model
Generating human motion from textual descriptions is a challenging task. Existing methods either struggle with physical credibility or are limited by the complexities of physics simulations. In this paper we present ReinDiffuse that comb... | [
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wacv_2025_c350d1e21a | c350d1e21a | wacv | 2,025 | Relational Self-Supervised Distillation with Compact Descriptors for Image Copy Detection | Image copy detection is the task of detecting edited copies of any image within a reference database. While previous approaches have shown remarkable progress the large size of their networks and descriptors remains a dis-advantage complicating their practical application. In this paper we propose a novel method that a... | Juntae Kim; Sungwon Woo; Jongho Nang | Sogang University; Sogang University; Sogang University + mAy-I | Poster | main | https://github.com/juntae9926/RDCD | https://openaccess.thecvf.com/content/WACV2025/html/Kim_Relational_Self-Supervised_Distillation_with_Compact_Descriptors_for_Image_Copy_Detection_WACV_2025_paper.html | 1 | 2405.17928 | Relational Self-Supervised Distillation with Compact Descriptors for Image Copy Detection
Image copy detection is the task of detecting edited copies of any image within a reference database. While previous approaches have shown remarkable progress the large size of their networks and descriptors remains a dis-advantag... | [
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wacv_2025_57ce1bad36 | 57ce1bad36 | wacv | 2,025 | Relaxing Binary Constraints in Contrastive Vision-Language Medical Representation Learning | By aligning paired image and caption embeddings as input contrastive vision-language representation learning has witnessed significant advances as illustrated by CLIP allowing visual encoders to learn from textual supervision and vice versa. Benefiting from millions of image-caption pairs collected from the Internet CL... | Xiaoyang Wei; Camille Kurtz; Florence Cloppet | Universit ´e Paris Cit ´e, LIPADE, F-75006, Paris, France; Universit ´e Paris Cit ´e, LIPADE, F-75006, Paris, France; Universit ´e Paris Cit ´e, LIPADE, F-75006, Paris, France | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wei_Relaxing_Binary_Constraints_in_Contrastive_Vision-Language_Medical_Representation_Learning_WACV_2025_paper.html | 0 | Relaxing Binary Constraints in Contrastive Vision-Language Medical Representation Learning
By aligning paired image and caption embeddings as input contrastive vision-language representation learning has witnessed significant advances as illustrated by CLIP allowing visual encoders to learn from textual supervision and... | [
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wacv_2025_4550a27d42 | 4550a27d42 | wacv | 2,025 | Remote Blood Pressure Estimation from Facial Videos using Transfer Learning: Leveraging PPG to rPPG Conversion | Blood pressure (BP) monitoring is crucial for health assessment but existing contact-based methods face cost and comfort barriers. Remote photoplethysmography (rPPG) offers a promising contactless solution yet research is hampered by limited rPPG datasets with corresponding BP labels. This paper presents a transfer lea... | Chun-Hong Cheng; Jing Wei Chin; Kwan Long Wong; Tsz Tai Chan; Hau Ching Lo; Kwan Lok Pang; Richard So; Bryan Yan | PanopticAI; PanopticAI + Hong Kong University of Science and Technology; PanopticAI + Hong Kong University of Science and Technology; PanopticAI + Hong Kong University of Science and Technology; Hong Kong University of Science and Technology; Hong Kong University of Science and Technology; Hong Kong University of Scien... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Cheng_Remote_Blood_Pressure_Estimation_from_Facial_Videos_using_Transfer_Learning_WACV_2025_paper.html | 0 | Remote Blood Pressure Estimation from Facial Videos using Transfer Learning: Leveraging PPG to rPPG Conversion
Blood pressure (BP) monitoring is crucial for health assessment but existing contact-based methods face cost and comfort barriers. Remote photoplethysmography (rPPG) offers a promising contactless solution yet... | [
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wacv_2025_bfbe260ede | bfbe260ede | wacv | 2,025 | Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation | One-class anomaly detection aims to detect objects that do not belong to a predefined normal class. In practice training data lack those anomalous samples; hence state-of-the-art methods are trained to discriminate between normal and synthetically-generated pseudo-anomalous data. Most methods use data augmentation tech... | Romain Hermary; Vincent Gaudilliere; Abd El Rahman Shabayek; Djamila Aouada | University of Luxembourg, Esch-sur-Alzette, Luxembourg; University of Luxembourg, Esch-sur-Alzette, Luxembourg; University of Luxembourg, Esch-sur-Alzette, Luxembourg; University of Luxembourg, Esch-sur-Alzette, Luxembourg | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Hermary_Removing_Geometric_Bias_in_One-Class_Anomaly_Detection_with_Adaptive_Feature_WACV_2025_paper.html | 0 | Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation
One-class anomaly detection aims to detect objects that do not belong to a predefined normal class. In practice training data lack those anomalous samples; hence state-of-the-art methods are trained to discriminate between normal ... | [
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wacv_2025_12ec89edb0 | 12ec89edb0 | wacv | 2,025 | RendBEV: Semantic Novel View Synthesis for Self-Supervised Bird's Eye View Segmentation | Bird's Eye View (BEV) semantic maps have recently garnered a lot of attention as a useful representation of the environment to tackle assisted and autonomous driving tasks. However most of the existing work focuses on the fully supervised setting training networks on large annotated datasets. In this work we present Re... | Henrique Piñeiro Monteagudo; Leonardo Taccari; Aurel Pjetri; Francesco Sambo; Samuele Salti | Verizon Connect, Italy+University of Bologna, Italy; Verizon Connect, Italy; University of Bologna, Italy+University of Florence, Italy; Verizon Connect, Italy; University of Bologna, Italy | Poster | main | https://henriquepm.github.io/RendBEV/ | https://openaccess.thecvf.com/content/WACV2025/html/Monteagudo_RendBEV_Semantic_Novel_View_Synthesis_for_Self-Supervised_Birds_Eye_View_WACV_2025_paper.html | 0 | RendBEV: Semantic Novel View Synthesis for Self-Supervised Bird's Eye View Segmentation
Bird's Eye View (BEV) semantic maps have recently garnered a lot of attention as a useful representation of the environment to tackle assisted and autonomous driving tasks. However most of the existing work focuses on the fully supe... | [
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wacv_2025_b09b0d2c70 | b09b0d2c70 | wacv | 2,025 | Retaining and Enhancing Pre-Trained Knowledge in Vision-Language Models with Prompt Ensembling | The advancement of vision-language models particularly the Contrastive Language-Image Pre-training (CLIP) model has revolutionized the field of machine learning by enabling robust zero-shot learning capabilities. These capabilities allow models to understand and respond to previously unseen data without task-specific t... | Donggeun Kim; Yujin Jo; Myungjoo Lee; Taesup Kim | Graduate School of Data Science, Seoul National University+Nota Inc.; Graduate School of Data Science, Seoul National University; Graduate School of Data Science, Seoul National University; Graduate School of Data Science, Seoul National University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kim_Retaining_and_Enhancing_Pre-Trained_Knowledge_in_Vision-Language_Models_with_Prompt_WACV_2025_paper.html | 0 | 2412.07077 | Retaining and Enhancing Pre-Trained Knowledge in Vision-Language Models with Prompt Ensembling
The advancement of vision-language models particularly the Contrastive Language-Image Pre-training (CLIP) model has revolutionized the field of machine learning by enabling robust zero-shot learning capabilities. These capabi... | [
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wacv_2025_edecbe631a | edecbe631a | wacv | 2,025 | Rethinking Cluster-Conditioned Diffusion Models for Label-Free Image Synthesis | Diffusion-based image generation models can enhance image quality when conditioned on ground truth labels. Here we conduct a comprehensive experimental study on image-level conditioning for diffusion models using cluster assignments. We investigate how individual clustering determinants such as the number of clusters a... | Nikolaos Adaloglou; Tim Kaiser; Felix Michels; Markus Kollmann | Heinrich Heine University of Dusseldorf; Heinrich Heine University of Dusseldorf; Heinrich Heine University of Dusseldorf; Heinrich Heine University of Dusseldorf | Poster | main | https://github.com/HHU-MMBS/cedm-official-wavc2025 | https://openaccess.thecvf.com/content/WACV2025/html/Adaloglou_Rethinking_Cluster-Conditioned_Diffusion_Models_for_Label-Free_Image_Synthesis_WACV_2025_paper.html | 0 | 2403.00570 | Rethinking Cluster-Conditioned Diffusion Models for Label-Free Image Synthesis
Diffusion-based image generation models can enhance image quality when conditioned on ground truth labels. Here we conduct a comprehensive experimental study on image-level conditioning for diffusion models using cluster assignments. We inve... | [
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wacv_2025_3d11aefb0f | 3d11aefb0f | wacv | 2,025 | Rethinking Low-Rank Adaptation in Vision: Exploring Head-Level Responsiveness Across Diverse Tasks | Low-rank adaptation (LoRA) has shifted the paradigm of adapting pre-trained Vision Transformers (ViT) achieving great efficiency by updating only a subset of tailored parameters to approximate weight updates. However the multi-head design of the self-attention mechanism with the heads working in parallel in the computa... | Yibo Zhong; Yao Zhou | Sichuan University; Sichuan University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhong_Rethinking_Low-Rank_Adaptation_in_Vision_Exploring_Head-Level_Responsiveness_Across_Diverse_WACV_2025_paper.html | 0 | 2404.08894 | Rethinking Low-Rank Adaptation in Vision: Exploring Head-Level Responsiveness Across Diverse Tasks
Low-rank adaptation (LoRA) has shifted the paradigm of adapting pre-trained Vision Transformers (ViT) achieving great efficiency by updating only a subset of tailored parameters to approximate weight updates. However the ... | [
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wacv_2025_700d590958 | 700d590958 | wacv | 2,025 | Retrieval Augmented Recipe Generation | The growing interest in generating recipes from food images has drawn substantial research attention in recent years. Existing works for recipe generation primarily utilize a two-stage training method--first predicting ingredients from a food image and then generating instructions from both the image and ingredients. L... | Guoshan Liu; Hailong Yin; Bin Zhu; Jingjing Chen; Chong-Wah Ngo; Yu-Gang Jiang | Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University+Shanghai Collaborative Innovation Center on Intelligent Visual Computing; Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University+Shanghai Collaborative Innovation Center on ... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Liu_Retrieval_Augmented_Recipe_Generation_WACV_2025_paper.html | 4 | 2411.08715 | Retrieval Augmented Recipe Generation
The growing interest in generating recipes from food images has drawn substantial research attention in recent years. Existing works for recipe generation primarily utilize a two-stage training method--first predicting ingredients from a food image and then generating instructions ... | [
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wacv_2025_0edac77902 | 0edac77902 | wacv | 2,025 | Reversing the Damage: A QP-Aware Transformer-Diffusion Approach for 8K Video Restoration under Codec Compression | In this paper we introduce DiQP; a novel Transformer-Diffusion model for restoring 8K video quality degraded by codec compression. To the best of our knowledge our model is the first to consider restoring the artifacts introduced by various codecs (AV1 HEVC) by Denoising Diffusion without considering additional noise. ... | Ali Mollaahmadi Dehaghi; Reza Razavi; Mohammad Moshirpour | University of Calgary; Userful Corporation; University of California, Irvine | Poster | main | https://github.com/alimd94/DiQP | https://openaccess.thecvf.com/content/WACV2025/html/Dehaghi_Reversing_the_Damage_A_QP-Aware_Transformer-Diffusion_Approach_for_8K_Video_WACV_2025_paper.html | 1 | 2412.08912 | Reversing the Damage: A QP-Aware Transformer-Diffusion Approach for 8K Video Restoration under Codec Compression
In this paper we introduce DiQP; a novel Transformer-Diffusion model for restoring 8K video quality degraded by codec compression. To the best of our knowledge our model is the first to consider restoring th... | [
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wacv_2025_cd7fb60021 | cd7fb60021 | wacv | 2,025 | Revisiting Deep Archetypal Analysis for Phenotype Discovery in High Content Imaging | The discovery of unique treatment candidates for complex diseases is a challenging task for current drug discovery programs. Biopharma research has developed automated and scalable screening assays of cell culture models to screen thousands of drug candidates in parallel e.g. by considering bio-image based assays. Howe... | Mario Wieser; Daniel Siegismund; Stephan Steigele | Genedata AG; Genedata AG; Genedata AG | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wieser_Revisiting_Deep_Archetypal_Analysis_for_Phenotype_Discovery_in_High_Content_WACV_2025_paper.html | 0 | Revisiting Deep Archetypal Analysis for Phenotype Discovery in High Content Imaging
The discovery of unique treatment candidates for complex diseases is a challenging task for current drug discovery programs. Biopharma research has developed automated and scalable screening assays of cell culture models to screen thous... | [
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wacv_2025_0d205785d7 | 0d205785d7 | wacv | 2,025 | Revisiting Disparity from Dual-Pixel Images: Physics-Informed Lightweight Depth Estimation | In this study we propose a high-performance disparity (depth) estimation method using dual-pixel (DP) images with few parameters. Conventional end-to-end deep-learning methods have many parameters but do not fully exploit disparity constraints which limits their performance. Therefore we propose a lightweight disparity... | Teppei Kurita; Yuhi Kondo; Legong Sun; Takayuki Sasaki; Sho Nitta; Yasuhiro Hashimoto; Yoshinori Muramatsu; Yusuke Moriuchi | ;;;;;;; | Poster | main | https://github.com/sony/dual-pixel-disparity | https://openaccess.thecvf.com/content/WACV2025/html/Kurita_Revisiting_Disparity_from_Dual-Pixel_Images_Physics-Informed_Lightweight_Depth_Estimation_WACV_2025_paper.html | 0 | 2411.04714 | Revisiting Disparity from Dual-Pixel Images: Physics-Informed Lightweight Depth Estimation
In this study we propose a high-performance disparity (depth) estimation method using dual-pixel (DP) images with few parameters. Conventional end-to-end deep-learning methods have many parameters but do not fully exploit dispari... | [
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wacv_2025_350e928640 | 350e928640 | wacv | 2,025 | Revisiting Machine Unlearning with Dimensional Alignment | Machine unlearning an emerging research topic focusing on data privacy compliance enables trained models to erase information learned from specific data. While many existing methods indirectly address this issue by intentionally injecting incorrect supervision they often result in drastic and unpredictable changes to d... | Seonguk Seo; Dongwan Kim; Bohyung Han | ECE; ECE; ECE+IPAI | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Seo_Revisiting_Machine_Unlearning_with_Dimensional_Alignment_WACV_2025_paper.html | 1 | 2407.17710 | Revisiting Machine Unlearning with Dimensional Alignment
Machine unlearning an emerging research topic focusing on data privacy compliance enables trained models to erase information learned from specific data. While many existing methods indirectly address this issue by intentionally injecting incorrect supervision th... | [
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wacv_2025_c6804d9e3f | c6804d9e3f | wacv | 2,025 | Reviving Poor Object Segmentations in OOD Medical Images using Variational-Deep-PCA Modeling on Segmentation Maps with Sampling-Free Learning | For object segmentation in medical images deep neural networks (DNNs) typically perform poorly on out-of-distribution (OOD) images stemming from the large variability in image-acquisition equipment and protocols across sites. However compared to such variability in the acquired medical images we observe that the variab... | Jimut B. Pal; Shantanu Welling; Himali Saini; Suyash P. Awate | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Pal_Reviving_Poor_Object_Segmentations_in_OOD_Medical_Images_using_Variational-Deep-PCA_WACV_2025_paper.html | 0 | Reviving Poor Object Segmentations in OOD Medical Images using Variational-Deep-PCA Modeling on Segmentation Maps with Sampling-Free Learning
For object segmentation in medical images deep neural networks (DNNs) typically perform poorly on out-of-distribution (OOD) images stemming from the large variability in image-ac... | [
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wacv_2025_619e3191dd | 619e3191dd | wacv | 2,025 | RiemStega: Covariance-Based Loss for Print-Proof Transmission of Data in Images | Covariance matrices outperform first-order features in many tasks attracting considerable attention from the computer vision research community. Covariance matrices encode second-order statistics between features at the same time it is robust to noise. Based on this we propose representing images by covariance matrices... | Aniana Cruz; Guilherme Schardong; Luiz Schirmer; João Marcos; Farhad Shadmand; Nuno Gonçalves | Institute of Systems and Robotics, University of Coimbra; Institute of Systems and Robotics, University of Coimbra; University of the Sinos River Valley; Institute of Systems and Robotics, University of Coimbra; Institute of Systems and Robotics, University of Coimbra; Institute of Systems and Robotics, University of C... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Cruz_RiemStega_Covariance-Based_Loss_for_Print-Proof_Transmission_of_Data_in_Images_WACV_2025_paper.html | 0 | RiemStega: Covariance-Based Loss for Print-Proof Transmission of Data in Images
Covariance matrices outperform first-order features in many tasks attracting considerable attention from the computer vision research community. Covariance matrices encode second-order statistics between features at the same time it is robu... | [
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wacv_2025_94ad84a225 | 94ad84a225 | wacv | 2,025 | Robot Instance Segmentation with Few Annotations for Grasping | The ability of robots to manipulate objects relies heavily on their aptitude for visual perception. In domains characterized by cluttered scenes and high object variability most methods call for vast labeled datasets laboriously hand-annotated with the aim of training capable models. Once deployed the challenge of gene... | Moshe Kimhi; David Vainshtein; Chaim Baskin; Dotan Di Castro | ;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kimhi_Robot_Instance_Segmentation_with_Few_Annotations_for_Grasping_WACV_2025_paper.html | 1 | 2407.01302 | Robot Instance Segmentation with Few Annotations for Grasping
The ability of robots to manipulate objects relies heavily on their aptitude for visual perception. In domains characterized by cluttered scenes and high object variability most methods call for vast labeled datasets laboriously hand-annotated with the aim o... | [
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wacv_2025_d1b28e143a | d1b28e143a | wacv | 2,025 | Robust Long-Range Perception Against Sensor Misalignment in Autonomous Vehicles | Advances in machine learning algorithms for sensor fusion have significantly improved the detection and prediction of other road users thereby enhancing safety. However even a small angular displacement in the sensor's placement can cause significant degradation in output especially at long range. In this paper we demo... | Zi-Xiang Xia; Sudeep Fadadu; Yi Shi; Louis Foucard | Aurora Innovation, Inc.; Aurora Innovation, Inc.; Aurora Innovation, Inc.; Aurora Innovation, Inc. | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Xia_Robust_Long-Range_Perception_Against_Sensor_Misalignment_in_Autonomous_Vehicles_WACV_2025_paper.html | 0 | 2408.11196 | Robust Long-Range Perception Against Sensor Misalignment in Autonomous Vehicles
Advances in machine learning algorithms for sensor fusion have significantly improved the detection and prediction of other road users thereby enhancing safety. However even a small angular displacement in the sensor's placement can cause s... | [
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wacv_2025_98d1e66318 | 98d1e66318 | wacv | 2,025 | Robust Novelty Detection through Style-Conscious Feature Ranking | Novelty detection seeks to identify samples deviating from a known distribution yet data shifts in a multitude of ways and only a few consist of relevant changes. Aligned with out-of-distribution generalization literature we advocate for a formal distinction between task-relevant semantic or content changes and irrelev... | Stefan Smeu; Elena Burceanu; Emanuela Haller; Andrei Liviu Nicolicioiu | Bitdefender, Bucharest, Romania; Bitdefender, Bucharest, Romania; Bitdefender, Bucharest, Romania; Mila and Université de Montréal, Montréal, Canada | Poster | main | https://github.com/bit-ml/Stylist | https://openaccess.thecvf.com/content/WACV2025/html/Smeu_Robust_Novelty_Detection_through_Style-Conscious_Feature_Ranking_WACV_2025_paper.html | 0 | 2310.03738 | Robust Novelty Detection through Style-Conscious Feature Ranking
Novelty detection seeks to identify samples deviating from a known distribution yet data shifts in a multitude of ways and only a few consist of relevant changes. Aligned with out-of-distribution generalization literature we advocate for a formal distinct... | [
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wacv_2025_a047a8aa94 | a047a8aa94 | wacv | 2,025 | Robust Portrait Image Matting and Depth-of-Field Synthesis via Multiplane Images | High-quality portrait photography has become an essential function in our daily lives. However due to the limited aperture and focal length of a smartphone camera images captured by a smartphone cannot match the same level of bokeh effect by a digital single-lens reflex camera. A typical solution on a smartphone is to ... | Zhefan Rao; Tianjia Zhang; Yuen Fui Lau; Qifeng Chen | Hong Kong University of Science and Technology; Hong Kong University of Science and Technology; Hong Kong University of Science and Technology; Hong Kong University of Science and Technology | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Rao_Robust_Portrait_Image_Matting_and_Depth-of-Field_Synthesis_via_Multiplane_Images_WACV_2025_paper.html | 0 | Robust Portrait Image Matting and Depth-of-Field Synthesis via Multiplane Images
High-quality portrait photography has become an essential function in our daily lives. However due to the limited aperture and focal length of a smartphone camera images captured by a smartphone cannot match the same level of bokeh effect ... | [
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wacv_2025_798f52d9a6 | 798f52d9a6 | wacv | 2,025 | RopeTP: Global Human Motion Recovery via Integrating Robust Pose Estimation with Diffusion Trajectory Prior | We present RopeTP a novel framework that combines Robust pose estimation with a diffusion Trajectory Prior to reconstruct global human motion from videos. At the heart of RopeTP is a hierarchical attention mechanism that significantly improves context awareness which is essential for accurately inferring the posture of... | Mingjiang Liang; Yongkang Cheng; Hualin Liang; Shaoli Huang; Wei Liu | ;;;; | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Liang_RopeTP_Global_Human_Motion_Recovery_via_Integrating_Robust_Pose_Estimation_WACV_2025_paper.html | 4 | 2410.20358 | RopeTP: Global Human Motion Recovery via Integrating Robust Pose Estimation with Diffusion Trajectory Prior
We present RopeTP a novel framework that combines Robust pose estimation with a diffusion Trajectory Prior to reconstruct global human motion from videos. At the heart of RopeTP is a hierarchical attention mechan... | [
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wacv_2025_d98ddc9fdd | d98ddc9fdd | wacv | 2,025 | Rubric-Constrained Figure Skating Scoring | Figure skating automatic scoring is the task of estimating the competition score of a performance video. The technical element score (TES) aggregates the technical quality (grade of execution) and difficulty (base value) scores for each element. Most prior work adapted from short-term action quality assessment entangle... | Arushi Rai; Adriana Kovashka | University of Pittsburgh; University of Pittsburgh | Poster | main | https://arushirai1.github.io/rcs-project | https://openaccess.thecvf.com/content/WACV2025/html/Rai_Rubric-Constrained_Figure_Skating_Scoring_WACV_2025_paper.html | 0 | Rubric-Constrained Figure Skating Scoring
Figure skating automatic scoring is the task of estimating the competition score of a performance video. The technical element score (TES) aggregates the technical quality (grade of execution) and difficulty (base value) scores for each element. Most prior work adapted from sho... | [
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wacv_2025_a2af271396 | a2af271396 | wacv | 2,025 | S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving | Recent self-supervised clustering-based pre-training techniques like DINO and CriBo have shown impressive results for downstream detection and segmentation tasks. However real-world applications such as autonomous driving face challenges with imbalanced object class and size distributions and complex scene geometries. ... | Maciej K. Wozniak; Hariprasath Govindarajan; Marvin Klingner; Camille Maurice; B Ravi Kiran; Senthil Yogamani | Automated Driving, Qualcomm Technologies International GmbH + KTH Royal Institute of Technology, Sweden; Arriver Software AB and Link ¨oping University, Sweden; Automated Driving, Qualcomm Technologies International GmbH; Automated Driving, Qualcomm Technologies International GmbH; Qualcomm SARL, France; Automated Driv... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wozniak_S3PT_Scene_Semantics_and_Structure_Guided_Clustering_to_Boost_Self-Supervised_WACV_2025_paper.html | 2 | 2410.23085 | S3PT: Scene Semantics and Structure Guided Clustering to Boost Self-Supervised Pre-Training for Autonomous Driving
Recent self-supervised clustering-based pre-training techniques like DINO and CriBo have shown impressive results for downstream detection and segmentation tasks. However real-world applications such as au... | [
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wacv_2025_820b2c3950 | 820b2c3950 | wacv | 2,025 | SADA: Semantic Adversarial Unsupervised Domain Adaptation for Temporal Action Localization | Temporal Action Localization (TAL) is a complex task that poses relevant challenges particularly when attempting to generalize on new - unseen - domains in real-world applications. These scenarios despite realistic are often neglected in the literature exposing these solutions to important performance degradation. In t... | David Pujol-Perich; Albert Clapés; Sergio Escalera | Universitat de Barcelona and Computer Vision Center, Barcelona, Spain; Universitat de Barcelona and Computer Vision Center, Barcelona, Spain; Universitat de Barcelona and Computer Vision Center, Barcelona, Spain | Poster | main | https://github.com/davidpujol/SADA | https://openaccess.thecvf.com/content/WACV2025/html/Pujol-Perich_SADA_Semantic_Adversarial_Unsupervised_Domain_Adaptation_for_Temporal_Action_Localization_WACV_2025_paper.html | 0 | SADA: Semantic Adversarial Unsupervised Domain Adaptation for Temporal Action Localization
Temporal Action Localization (TAL) is a complex task that poses relevant challenges particularly when attempting to generalize on new - unseen - domains in real-world applications. These scenarios despite realistic are often negl... | [
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wacv_2025_2b3b2415b1 | 2b3b2415b1 | wacv | 2,025 | SADDLe: Sharpness-Aware Decentralized Deep Learning with Heterogeneous Data | Decentralized training enables learning with distributed datasets generated at different locations without relying on a central server. In realistic scenarios the data distribution across these sparsely connected learning agents can be significantly heterogeneous leading to local model over-fitting and poor global mode... | Sakshi Choudhary; Sai Aparna Aketi; Kaushik Roy | Purdue University; Purdue University; Purdue University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Choudhary_SADDLe_Sharpness-Aware_Decentralized_Deep_Learning_with_Heterogeneous_Data_WACV_2025_paper.html | 0 | 2405.13961 | SADDLe: Sharpness-Aware Decentralized Deep Learning with Heterogeneous Data
Decentralized training enables learning with distributed datasets generated at different locations without relying on a central server. In realistic scenarios the data distribution across these sparsely connected learning agents can be signific... | [
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wacv_2025_5142fc27c1 | 5142fc27c1 | wacv | 2,025 | SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-Grade Videos | Managing chronic wounds is a global challenge that can be alleviated by the adoption of automatic systems for clinical wound assessment from consumer-grade videos. While 2D image analysis approaches are insufficient for handling the 3D features of wounds existing approaches utilizing 3D reconstruction methods have not ... | Remi Chierchia; Leo Lebrat; David Ahmedt-Aristizabal; Olivier Salvado; Clinton Fookes; Rodrigo Santa Cruz | ;;;;; | Poster | main | https://remichierchia.github.io/SALVE/ | https://openaccess.thecvf.com/content/WACV2025/html/Chierchia_SALVE_A_3D_Reconstruction_Benchmark_of_Wounds_from_Consumer-Grade_Videos_WACV_2025_paper.html | 0 | 2407.19652 | SALVE: A 3D Reconstruction Benchmark of Wounds from Consumer-Grade Videos
Managing chronic wounds is a global challenge that can be alleviated by the adoption of automatic systems for clinical wound assessment from consumer-grade videos. While 2D image analysis approaches are insufficient for handling the 3D features o... | [
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wacv_2025_00dcdce1fc | 00dcdce1fc | wacv | 2,025 | SAM-DA: Decoder Adapter for Efficient Medical Domain Adaptation | This paper addresses the domain adaptation challenge for semantic segmentation in medical imaging. Despite the impressive performance of recent foundational segmentation models like SAM on natural images they struggle with medical domain images. Beyond this recent approaches that perform end-to-end fine-tuning of model... | Javier Gamazo Tejero; Moritz J Schmid; Pablo Márquez Neila; Martin Zinkernagel; Sebastian Wolf; Raphael Sznitman | University of Bern; University of Bern; University of Bern; Inselspital Bern; Inselspital Bern; University of Bern | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Tejero_SAM-DA_Decoder_Adapter_for_Efficient_Medical_Domain_Adaptation_WACV_2025_paper.html | 0 | SAM-DA: Decoder Adapter for Efficient Medical Domain Adaptation
This paper addresses the domain adaptation challenge for semantic segmentation in medical imaging. Despite the impressive performance of recent foundational segmentation models like SAM on natural images they struggle with medical domain images. Beyond thi... | [
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wacv_2025_abb0427f7f | abb0427f7f | wacv | 2,025 | SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation | Polyp segmentation in colonoscopy images is crucial for detecting colorectal cancer but is challenging due to variations in the structure color and size of polyps as well as the lack of clear boundaries with surrounding tissues. Traditional segmentation models based on Convolutional Neural Networks (CNNs) struggle to c... | Tapas Kumar Dutta; Snehashis Majhi; Deepak Ranjan Nayak; Debesh Jha | University of Surrey, United Kingdom; Côte d’Azur University, France; Malaviya National Institute of Technology Jaipur, India; University of South Dakota, USA | Poster | main | https://github.com/TapasKumarDutta1/SAM_Mamba_2025 | https://openaccess.thecvf.com/content/WACV2025/html/Dutta_SAM-Mamba_Mamba_Guided_SAM_Architecture_for_Generalized_Zero-Shot_Polyp_Segmentation_WACV_2025_paper.html | 1 | SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation
Polyp segmentation in colonoscopy images is crucial for detecting colorectal cancer but is challenging due to variations in the structure color and size of polyps as well as the lack of clear boundaries with surrounding tissues. Tradi... | [
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wacv_2025_67d0ab5d3a | 67d0ab5d3a | wacv | 2,025 | SAND: Enhancing Open-Set Neuron Descriptions through Spatial Awareness | We propose Spatially-Aware open-set Network Dissection (SAND) a technique to identify and label the learned representation of the neurons of deep vision networks. Contrary to earlier open-vocabulary neuron explanation methods we also leverage a neuron's spatial pattern of activation to guide our predictions towards mor... | Anvita Agarwal Srinivas; Tuomas Oikarinen; Divyansh Srivastava; Wei-Hung Weng; Tsui-Wei Weng | University of California San Diego; University of California San Diego; University of California San Diego; Google Research; University of California San Diego | Poster | main | https://github.com/Trustworthy-ML-Lab/SAND | https://openaccess.thecvf.com/content/WACV2025/html/Srinivas_SAND_Enhancing_Open-Set_Neuron_Descriptions_through_Spatial_Awareness_WACV_2025_paper.html | 0 | SAND: Enhancing Open-Set Neuron Descriptions through Spatial Awareness
We propose Spatially-Aware open-set Network Dissection (SAND) a technique to identify and label the learned representation of the neurons of deep vision networks. Contrary to earlier open-vocabulary neuron explanation methods we also leverage a neur... | [
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wacv_2025_6946f9ad02 | 6946f9ad02 | wacv | 2,025 | SANPO: A Scene Understanding Accessibility and Human Navigation Dataset | Vision is essential for human navigation. The World Health Organization (WHO) estimates that 43.3 million people were blind in 2020 and this number is projected to reach 61 million by 2050. Modern scene understanding models could empower these people by assisting them with navigation obstacle avoidance and visual recog... | Sagar M. Waghmare; Kimberly Wilber; Dave Hawkey; Xuan Yang; Matthew Wilson; Stephanie Debats; Cattalyya Nuengsigkapian; Astuti Sharma; Lars Pandikow; Huisheng Wang; Hartwig Adam; Mikhail Sirotenko | Google Research; Google Research; Google Research; Google Research; Google Research; Google Research; Google Research; Google Research; Parallel Domain; Google Research; Google Research; Google Research | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Waghmare_SANPO_A_Scene_Understanding_Accessibility_and_Human_Navigation_Dataset_WACV_2025_paper.html | 1 | 2309.12172 | SANPO: A Scene Understanding Accessibility and Human Navigation Dataset
Vision is essential for human navigation. The World Health Organization (WHO) estimates that 43.3 million people were blind in 2020 and this number is projected to reach 61 million by 2050. Modern scene understanding models could empower these peop... | [
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wacv_2025_56fbcc6ed8 | 56fbcc6ed8 | wacv | 2,025 | SCOT: Self-Supervised Contrastive Pretraining for Zero-Shot Compositional Retrieval | Compositional image retrieval (CIR) is a multimodal learning task where a model combines a query image with a user-provided text modification to retrieve a target image. CIR finds applications in a variety of domains including product retrieval (e-commerce) and web search. Existing methods primarily focus on fully-supe... | Bhavin Jawade; João V. B. Soares; Kapil Thadani; Deen Dayal Mohan; Amir Erfan Eshratifar; Benjamin Culpepper; Paloma de Juan; Srirangaraj Setlur; Venu Govindaraju | Yahoo Research+University at Buffalo, SUNY; Yahoo Research; Yahoo Research; Yahoo Research; Yahoo Research; Yahoo Research; Yahoo Research; University at Buffalo, SUNY; University at Buffalo, SUNY | Poster | main | https://github.com/yahoo/SCOT | https://openaccess.thecvf.com/content/WACV2025/html/Jawade_SCOT_Self-Supervised_Contrastive_Pretraining_for_Zero-Shot_Compositional_Retrieval_WACV_2025_paper.html | 0 | 2501.08347 | SCOT: Self-Supervised Contrastive Pretraining for Zero-Shot Compositional Retrieval
Compositional image retrieval (CIR) is a multimodal learning task where a model combines a query image with a user-provided text modification to retrieve a target image. CIR finds applications in a variety of domains including product r... | [
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wacv_2025_ac5b67c17f | ac5b67c17f | wacv | 2,025 | SEED4D: A Synthetic Ego-Exo Dynamic 4D Data Generator Driving Dataset and Benchmark | Models for egocentric 3D and 4D reconstruction including few-shot interpolation and extrapolation settings can benefit from having images from exocentric viewpoints as supervision signals. No existing dataset provides the necessary mixture of complex dynamic and multi-view data. To facilitate the development of 3D and ... | Marius Kästingschäfer; Théo Gieruc; Sebastian Bernhard; Dylan Campbell; Eldar Insafutdinov; Eyvaz Najafli; Thomas Brox | Continental + University of Freiburg; Continental; Continental; Australian National University; University of Oxford; Continental + University of T ¨ubingen; University of Freiburg | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kastingschafer_SEED4D_A_Synthetic_Ego-Exo_Dynamic_4D_Data_Generator_Driving_Dataset_WACV_2025_paper.html | 2 | SEED4D: A Synthetic Ego-Exo Dynamic 4D Data Generator Driving Dataset and Benchmark
Models for egocentric 3D and 4D reconstruction including few-shot interpolation and extrapolation settings can benefit from having images from exocentric viewpoints as supervision signals. No existing dataset provides the necessary mixt... | [
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wacv_2025_7bf5b2c0ba | 7bf5b2c0ba | wacv | 2,025 | SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM | Image inpainting aims to repair a partially damaged image based on the information from known regions of the images. Achieving semantically plausible inpainting results is particularly challenging because it requires the reconstructed regions to exhibit similar patterns to the semantically consistent regions. This requ... | Shuang Chen; Haozheng Zhang; Amir Atapour-Abarghouei; Hubert P. H. Shum | Durham University; Durham University; Durham University; Durham University | Poster | main | https://github.com/ChrisChen1023/SEM-Net | https://openaccess.thecvf.com/content/WACV2025/html/Chen_SEM-Net_Efficient_Pixel_Modelling_for_Image_Inpainting_with_Spatially_Enhanced_WACV_2025_paper.html | 0 | SEM-Net: Efficient Pixel Modelling for Image Inpainting with Spatially Enhanced SSM
Image inpainting aims to repair a partially damaged image based on the information from known regions of the images. Achieving semantically plausible inpainting results is particularly challenging because it requires the reconstructed r... | [
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wacv_2025_9d1e81f544 | 9d1e81f544 | wacv | 2,025 | SEMU-Net: A Segmentation-Based Corrector for Fabrication Process Variations of Nanophotonics with Microscopic Images | Integrated silicon photonic devices which manipulate light to transmit and process information on a silicon-on-insulator chip are highly sensitive to structural variations. Minor deviations during nanofabrication--the precise process of building structures at the nanometer scale--such as over- or under-etching corner r... | Rambod Azimi; Yijian Kong; Dusan Gostimirovic; James J. Clark; Odile Liboiron-Ladouceur | McGill University; McGill University; McGill University; McGill University; McGill University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Azimi_SEMU-Net_A_Segmentation-Based_Corrector_for_Fabrication_Process_Variations_of_Nanophotonics_WACV_2025_paper.html | 0 | SEMU-Net: A Segmentation-Based Corrector for Fabrication Process Variations of Nanophotonics with Microscopic Images
Integrated silicon photonic devices which manipulate light to transmit and process information on a silicon-on-insulator chip are highly sensitive to structural variations. Minor deviations during nanofa... | [
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wacv_2025_a9e6b10498 | a9e6b10498 | wacv | 2,025 | SGD: Street View Synthesis with Gaussian Splatting and Diffusion Prior | Novel View Synthesis (NVS) for street scenes plays a critical role in the autonomous driving simulation. Current mainstream methods such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) struggle to maintain rendering quality at the viewpoint that deviates significantly from the training viewpoints. Thi... | Zhongrui Yu; Haoran Wang; Jinze Yang; Hanzhang Wang; Jiale Cao; Zhong Ji; Mingming Sun | ETH Zürich; Baidu Research; University of Chinese Academy of Sciences; Harbin Institute of Technology; Tianjin University; Tianjin University; BIMSA | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Yu_SGD_Street_View_Synthesis_with_Gaussian_Splatting_and_Diffusion_Prior_WACV_2025_paper.html | 18 | 2403.20079 | SGD: Street View Synthesis with Gaussian Splatting and Diffusion Prior
Novel View Synthesis (NVS) for street scenes plays a critical role in the autonomous driving simulation. Current mainstream methods such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) struggle to maintain rendering quality at the ... | [
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wacv_2025_dbe70f86d6 | dbe70f86d6 | wacv | 2,025 | SHIP: Structural Hierarchies for Instance-Dependent Partial Labels | Partial label learning (PLL) aims to train classification models under conditions where each training sample is associated with a candidate set of labels. This set contains multiple labels among which only one is correct. This work addresses instance-dependent noise in PLL by leveraging hierarchical structures within t... | Tushar Kadam; Utkarsh Mishra; Aakarsh Malhotra | AI Garage, Mastercard, Gurugram, Haryana, India; AI Garage, Mastercard, Gurugram, Haryana, India; AI Garage, Mastercard, Gurugram, Haryana, India | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kadam_SHIP_Structural_Hierarchies_for_Instance-Dependent_Partial_Labels_WACV_2025_paper.html | 0 | SHIP: Structural Hierarchies for Instance-Dependent Partial Labels
Partial label learning (PLL) aims to train classification models under conditions where each training sample is associated with a candidate set of labels. This set contains multiple labels among which only one is correct. This work addresses instance-de... | [
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wacv_2025_48bfc75dba | 48bfc75dba | wacv | 2,025 | SIGNN - Star Identification using Graph Neural Networks | As a solution for the lost-in-space star identification problem we present Star Identification using Graph Neural Network (SIGNN) a novel approach using Graph Attention Networks. By representing the celestial sphere as a graph data structure created from the ESA's Hipparcos catalogue we are able to accurately capture t... | Floyd Hepburn-Dickins; Mark W. Jones; Mike Edwards; Jay Paul Morgan; Steve Bell | Swansea University, United Kingdom; Swansea University, United Kingdom; Swansea University, United Kingdom; Swansea University, United Kingdom; UK Hydrographic Office, Taunton, Somerset, United Kingdom | Poster | main | https://github.com/FloydHepburn/SIGNN | https://openaccess.thecvf.com/content/WACV2025/html/Hepburn-Dickins_SIGNN_-_Star_Identification_using_Graph_Neural_Networks_WACV_2025_paper.html | 0 | SIGNN - Star Identification using Graph Neural Networks
As a solution for the lost-in-space star identification problem we present Star Identification using Graph Neural Network (SIGNN) a novel approach using Graph Attention Networks. By representing the celestial sphere as a graph data structure created from the ESA's... | [
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wacv_2025_315bda727b | 315bda727b | wacv | 2,025 | SMDAF: A Scalable Sidewalk Material Data Acquisition Framework with Bidirectional Cross-Modal Knowledge Distillation | Ensuring safe and independent navigation poses considerable difficulties for individuals who are blind or have low vision (BLV) as it requires detailed knowledge of their immediate environment. Our research highlights the critical need for accessible data on sidewalk materials and objects which is currently lacking in ... | Jiawei Liu; Wayne Lam; Zhigang Zhu; Hao Tang | The Graduate Center - CUNY; The City College of New York - CUNY; The Graduate Center - CUNY + The City College of New York - CUNY; The Graduate Center - CUNY + Borough of Manhattan Community College - CUNY | Poster | main | https://github.com/FgSurewin/SMDAF-CMKD | https://openaccess.thecvf.com/content/WACV2025/html/Liu_SMDAF_A_Scalable_Sidewalk_Material_Data_Acquisition_Framework_with_Bidirectional_WACV_2025_paper.html | 1 | SMDAF: A Scalable Sidewalk Material Data Acquisition Framework with Bidirectional Cross-Modal Knowledge Distillation
Ensuring safe and independent navigation poses considerable difficulties for individuals who are blind or have low vision (BLV) as it requires detailed knowledge of their immediate environment. Our resea... | [
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wacv_2025_0307063f49 | 0307063f49 | wacv | 2,025 | SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models | Adapting large-scale pre-trained generative models in a parameter-efficient manner is gaining traction. Traditional methods like low rank adaptation achieve parameter efficiency by imposing constraints but may not be optimal for tasks requiring high representation capacity. We propose a novel spectrum-aware adaptation ... | Xinxi Zhang; Song Wen; Ligong Han; Felix Juefei-Xu; Akash Srivastava; Junzhou Huang; Vladimir Pavlovic; Hao Wang; Molei Tao; Dimitris Metaxas | Rutgers University; Rutgers University; Rutgers University+New York University; New York University; MIT-IBM Watson AI Lab; UT Arlington; Rutgers University; Rutgers University; Georgia Tech; Rutgers University | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Zhang_SODA_Spectral_Orthogonal_Decomposition_Adaptation_for_Diffusion_Models_WACV_2025_paper.html | 0 | SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models
Adapting large-scale pre-trained generative models in a parameter-efficient manner is gaining traction. Traditional methods like low rank adaptation achieve parameter efficiency by imposing constraints but may not be optimal for tasks requiring hig... | [
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wacv_2025_2bb6693de8 | 2bb6693de8 | wacv | 2,025 | SPACE: SPAtial-Aware Consistency rEgularization for Anomaly Detection in Industrial Applications | In this paper we propose SPACE a novel anomaly detection methodology that integrates a Feature Encoder (FE) into the structure of the Student-Teacher method. The proposed method has two key elements: Spatial Consistency regularization Loss (SCL) and Feature converter Module (FM). SCL prevents overfitting in student mod... | Daehwan Kim; Hyungmin Kim; Daun Jeong; Sungho Suh; Hansang Cho | Samsung Electro-Mechanics, Suwon, Republic of Korea; Samsung Electro-Mechanics, Suwon, Republic of Korea; Samsung Electro-Mechanics, Suwon, Republic of Korea; German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany+Department of Computer Science, RPTU Kaiserslautern-Landau, Kaiserslautern, Ge... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Kim_SPACE_SPAtial-Aware_Consistency_rEgularization_for_Anomaly_Detection_in_Industrial_Applications_WACV_2025_paper.html | 0 | 2411.05822 | SPACE: SPAtial-Aware Consistency rEgularization for Anomaly Detection in Industrial Applications
In this paper we propose SPACE a novel anomaly detection methodology that integrates a Feature Encoder (FE) into the structure of the Student-Teacher method. The proposed method has two key elements: Spatial Consistency reg... | [
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wacv_2025_29d86ca6d0 | 29d86ca6d0 | wacv | 2,025 | STAY Diffusion: Styled Layout Diffusion Model for Diverse Layout-to-Image Generation | In layout-to-image (L2I) synthesis controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the generation process while remaining easily reconfigurable by humans. In this paper we prop... | Ruyu Wang; Xuefeng Hou; Sabrina Schmedding; Marco Huber | Bosch Center for Artificial Intelligence, Renningen, Germany+Institute of Industrial Manufacturing and Management IFF, University of Stuttgart, Stuttgart, Germany; Bosch Center for Artificial Intelligence, Renningen, Germany; Bosch Center for Artificial Intelligence, Renningen, Germany; Institute of Industrial Manufact... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Wang_STAY_Diffusion_Styled_Layout_Diffusion_Model_for_Diverse_Layout-to-Image_Generation_WACV_2025_paper.html | 0 | STAY Diffusion: Styled Layout Diffusion Model for Diverse Layout-to-Image Generation
In layout-to-image (L2I) synthesis controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the gene... | [
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wacv_2025_26a292a8b5 | 26a292a8b5 | wacv | 2,025 | STLight: A Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal Joint Processing | Spatio-Temporal predictive Learning is a self-supervised learning paradigm that enables models to identify spatial and temporal patterns by predicting future frames based on past frames. Traditional methods which use recurrent neural networks to capture temporal patterns have proven their effectiveness but come with hi... | Andrea Alfarano; Alberto Alfarano; Linda Friso; Andrea Bacciu; Irene Amerini; Fabrizio Silvestri | DVS, University of Zurich+Max Planck Society; Meta; Google; Sapienza, University of Rome; Sapienza, University of Rome; Sapienza, University of Rome | Poster | main | https://github.com/AlfaranoAndrea/STLight/ | https://openaccess.thecvf.com/content/WACV2025/html/Alfarano_STLight_A_Fully_Convolutional_Approach_for_Efficient_Predictive_Learning_by_WACV_2025_paper.html | 1 | 2411.10198 | STLight: A Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal Joint Processing
Spatio-Temporal predictive Learning is a self-supervised learning paradigm that enables models to identify spatial and temporal patterns by predicting future frames based on past frames. Traditional methods whi... | [
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wacv_2025_5d1bd97253 | 5d1bd97253 | wacv | 2,025 | STRIDE: Single-Video Based Temporally Continuous Occlusion-Robust 3D Pose Estimation | The capability to accurately estimate 3D human poses is crucial for diverse fields such as action recognition gait recognition and virtual/augmented reality. However a persistent and significant challenge within this field is the accurate prediction of human poses under conditions of severe occlusion. Traditional image... | Rohit Lal; Saketh Bachu; Yash Garg; Arindam Dutta; Calvin-Khang Ta; Hannah Dela Cruz; Dripta S. Raychaudhuri; M. Salman Asif; Amit Roy-Chowdhury | University of California, Riverside‡; University of California, Riverside∗; University of California, Riverside; University of California, Riverside; University of California, Riverside; University of California, Riverside; University of California, Riverside†; University of California, Riverside; University of Califor... | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Lal_STRIDE_Single-Video_Based_Temporally_Continuous_Occlusion-Robust_3D_Pose_Estimation_WACV_2025_paper.html | 0 | 2312.16221 | STRIDE: Single-Video Based Temporally Continuous Occlusion-Robust 3D Pose Estimation
The capability to accurately estimate 3D human poses is crucial for diverse fields such as action recognition gait recognition and virtual/augmented reality. However a persistent and significant challenge within this field is the accur... | [
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wacv_2025_bd6e5d3142 | bd6e5d3142 | wacv | 2,025 | SUM: Saliency Unification through Mamba for Visual Attention Modeling | Visual attention modeling important for interpreting and prioritizing visual stimuli plays a significant role in applications such as marketing multimedia and robotics. Traditional saliency prediction models especially those based on Convolutional Neural Networks (CNNs) or Transformers achieve notable success by levera... | Alireza Hosseini; Amirhossein Kazerouni; Saeed Akhavan; Michael Brudno; Babak Taati | University of Tehran; University of Toronto+Vector Institute+University Health Network; University of Tehran; University of Toronto+Vector Institute+University Health Network; University of Toronto+Vector Institute+University Health Network | Poster | main | https://arhosseini77.github.io/sum_page/ | https://openaccess.thecvf.com/content/WACV2025/html/Hosseini_SUM_Saliency_Unification_through_Mamba_for_Visual_Attention_Modeling_WACV_2025_paper.html | 11 | 2406.17815 | SUM: Saliency Unification through Mamba for Visual Attention Modeling
Visual attention modeling important for interpreting and prioritizing visual stimuli plays a significant role in applications such as marketing multimedia and robotics. Traditional saliency prediction models especially those based on Convolutional Ne... | [
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wacv_2025_51360bd67e | 51360bd67e | wacv | 2,025 | SV-data2vec: Guiding Video Representation Learning with Latent Skeleton Targets | Recent advancements in action recognition leverage both skeleton and video modalities to achieve state-of-the-art performance. However due to the challenges of early fusion which tends to underutilize the strengths of each modality existing methods often resort to late fusion consequently leading to more complex design... | Zorana Doždor; Tomislav Hrkac; Zoran Kalafatic | University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia; University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia; University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia | Poster | main | github.com/zoranadozdor/SVdata2vec | https://openaccess.thecvf.com/content/WACV2025/html/Dozdor_SV-data2vec_Guiding_Video_Representation_Learning_with_Latent_Skeleton_Targets_WACV_2025_paper.html | 0 | SV-data2vec: Guiding Video Representation Learning with Latent Skeleton Targets
Recent advancements in action recognition leverage both skeleton and video modalities to achieve state-of-the-art performance. However due to the challenges of early fusion which tends to underutilize the strengths of each modality existing... | [
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wacv_2025_dceb639235 | dceb639235 | wacv | 2,025 | Scene-LLM: Extending Language Model for 3D Visual Reasoning | This paper introduces Scene-LLM a 3D-visual-language model that enhances embodied agents' abilities in interactive 3D indoor environments by integrating the reasoning strengths of Large Language Models (LLMs). Scene-LLM adopts a unified 3D visual feature representation that incorporates dense spatial information and su... | Rao Fu; Jingyu Liu; Xilun Chen; Yixin Nie; Wenhan Xiong | Brown University; University of Chicago; Meta AI; Meta AI; Meta AI | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Fu_Scene-LLM_Extending_Language_Model_for_3D_Visual_Reasoning_WACV_2025_paper.html | 2 | Scene-LLM: Extending Language Model for 3D Visual Reasoning
This paper introduces Scene-LLM a 3D-visual-language model that enhances embodied agents' abilities in interactive 3D indoor environments by integrating the reasoning strengths of Large Language Models (LLMs). Scene-LLM adopts a unified 3D visual feature repre... | [
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wacv_2025_1bea982769 | 1bea982769 | wacv | 2,025 | SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution | Implicit Neural Representations (INRs) have recently advanced the field of deep learning due to their ability to learn continuous representations of signals without the need for large training datasets. Although INR methods have been studied for medical image super-resolution their adaptability to localized priors in m... | Mevan Ekanayake; Zhifeng Chen; Gary Egan; Mehrtash Harandi; Zhaolin Chen | Monash University, Melbourne, Australia; Monash University, Melbourne, Australia; Monash University, Melbourne, Australia; Monash University, Melbourne, Australia; Monash University, Melbourne, Australia | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Ekanayake_SeCo-INR_Semantically_Conditioned_Implicit_Neural_Representations_for_Improved_Medical_Image_WACV_2025_paper.html | 0 | SeCo-INR: Semantically Conditioned Implicit Neural Representations for Improved Medical Image Super-Resolution
Implicit Neural Representations (INRs) have recently advanced the field of deep learning due to their ability to learn continuous representations of signals without the need for large training datasets. Althou... | [
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wacv_2025_6383f8c4a1 | 6383f8c4a1 | wacv | 2,025 | Secrets of Edge-Informed Contrast Maximization for Event-Based Vision | Event cameras capture the motion of intensity gradients (edges) in the image plane in the form of rapid asynchronous events. When accumulated in 2D histograms these events depict overlays of the edges in motion consequently obscuring the spatial structure of the generating edges. Contrast maximization (CM) is an optimi... | Pritam P. Karmokar; Quan H. Nguyen; William J. Beksi | The University of Texas at Arlington; The University of Texas at Arlington; The University of Texas at Arlington | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Karmokar_Secrets_of_Edge-Informed_Contrast_Maximization_for_Event-Based_Vision_WACV_2025_paper.html | 1 | 2409.14611 | Secrets of Edge-Informed Contrast Maximization for Event-Based Vision
Event cameras capture the motion of intensity gradients (edges) in the image plane in the form of rapid asynchronous events. When accumulated in 2D histograms these events depict overlays of the edges in motion consequently obscuring the spatial stru... | [
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wacv_2025_de039c8de2 | de039c8de2 | wacv | 2,025 | Seeing Eye to AI: Comparing Human Gaze and Model Attention in Video Memorability | Understanding what makes a video memorable has important applications in advertising and education technology. Towards this goal we investigate spatio-temporal attention mechanisms underlying video memorability. Different from previous works that fuse multiple features we adopt a simple CNN+Transformer architecture tha... | Prajneya Kumar; Eshika Khandelwal; Makarand Tapaswi; Vishnu Sreekumar | Cognitive Science Lab; CVIT; CVIT; Cognitive Science Lab | Poster | main | https://github.com/katha-ai/video-memorability | https://openaccess.thecvf.com/content/WACV2025/html/Kumar_Seeing_Eye_to_AI_Comparing_Human_Gaze_and_Model_Attention_WACV_2025_paper.html | 1 | 2311.16484 | Seeing Eye to AI: Comparing Human Gaze and Model Attention in Video Memorability
Understanding what makes a video memorable has important applications in advertising and education technology. Towards this goal we investigate spatio-temporal attention mechanisms underlying video memorability. Different from previous wor... | [
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wacv_2025_2261cba6c4 | 2261cba6c4 | wacv | 2,025 | SegBuilder: A Semi-Automatic Annotation Tool for Segmentation | This paper addresses the problem of image annotation for segmentation tasks. Semantic segmentation involves labeling each pixel in an image with predefined categories such as sky cars roads and humans. Deep learning models require numerous annotated images for effective training but manual annotation is slow and time-c... | Md Alimoor Reza; Eric Manley; Sean Chen; Sameer Chaudhary; Jacob Elafros | Drake University, Des Moines, Iowa, USA; Drake University, Des Moines, Iowa, USA; Drake University, Des Moines, Iowa, USA; Drake University, Des Moines, Iowa, USA; Drake University, Des Moines, Iowa, USA | Poster | main | https://github.com/alimoorreza/segbuilder-v1 | https://openaccess.thecvf.com/content/WACV2025/html/Reza_SegBuilder_A_Semi-Automatic_Annotation_Tool_for_Segmentation_WACV_2025_paper.html | 0 | SegBuilder: A Semi-Automatic Annotation Tool for Segmentation
This paper addresses the problem of image annotation for segmentation tasks. Semantic segmentation involves labeling each pixel in an image with predefined categories such as sky cars roads and humans. Deep learning models require numerous annotated images f... | [
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wacv_2025_6bee39bf60 | 6bee39bf60 | wacv | 2,025 | SegDesicNet: Lightweight Semantic Segmentation in Remote Sensing with Geo-Coordinate Embeddings for Domain Adaptation | Semantic segmentation is essential for analyzing high-definition remote sensing images (HRSIs) because it allows the precise classification of objects and regions at the pixel level. However remote sensing data present challenges owing to geographical location weather and environmental variations making it difficult fo... | Sachin Verma; Frank Lindseth; Gabriel Kiss | Norwegian University of Science and Technology (NTNU), Norway; Norwegian University of Science and Technology (NTNU), Norway; Norwegian University of Science and Technology (NTNU), Norway | Poster | main | https://openaccess.thecvf.com/content/WACV2025/html/Verma_SegDesicNet_Lightweight_Semantic_Segmentation_in_Remote_Sensing_with_Geo-Coordinate_Embeddings_WACV_2025_paper.html | 0 | SegDesicNet: Lightweight Semantic Segmentation in Remote Sensing with Geo-Coordinate Embeddings for Domain Adaptation
Semantic segmentation is essential for analyzing high-definition remote sensing images (HRSIs) because it allows the precise classification of objects and regions at the pixel level. However remote sens... | [
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wacv_2025_20086d7921 | 20086d7921 | wacv | 2,025 | Segment Anything Meets Point Tracking | Foundation models have marked a significant stride toward addressing generalization challenges in deep learning. While the Segment Anything Model (SAM) has established a strong foothold in image segmentation existing video segmentation methods still require extensive mask labeling for fine-tuning or face performance dr... | Frano Rajič; Lei Ke; Yu-Wing Tai; Chi-Keung Tang; Martin Danelljan; Fisher Yu | ETH Z ¨urich; ETH Z ¨urich; HKUST; HKUST; ETH Z ¨urich; ETH Z ¨urich | Poster | main | https://github.com/SysCV/sam-pt | https://openaccess.thecvf.com/content/WACV2025/html/Rajic_Segment_Anything_Meets_Point_Tracking_WACV_2025_paper.html | 80 | Segment Anything Meets Point Tracking
Foundation models have marked a significant stride toward addressing generalization challenges in deep learning. While the Segment Anything Model (SAM) has established a strong foothold in image segmentation existing video segmentation methods still require extensive mask labeling ... | [
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