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Anti-spoofing Dataset
The dataset consists of 4,714 videos from 4,714 people, each featuring real faces recorded via personal computers. Designed for training data generation and benchmark recognition tasks, it offers diverse spoofing attacks and attack scenarios essential for evaluating facial recognition and liveness detection performance.
By including a wide range of replay attacks and video recordings in MP4 and MOV formats, this dataset supports the development and validation of anti-spoofing technology, recognition algorithms, and biometric systems. - Get the data
Each clip is annotated with age, gender, and ethnicity labels, allowing researchers to build detection algorithms that generalize across different subjects and device types.
💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.
Researchers can use this dataset to study spoofing attempts, fake faces, and photos attacks, improving the resilience of recognition systems and security technology. The dataset supports a wide range of attack detection tasks, helping innovators design more effective anti-spoofing solutions that enhance identity verification, biometric security, and overall computer vision performance.
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