Multi-Frames Temporal Abnormal Clues Learning Method for Face Anti-Spoofing
نویسندگان
چکیده
Face anti-spoofing researches are widely used in face recognition and has received more attention from industry academics. In this paper, we propose the EulerNet, a new temporal feature fusion network which differential filter residual pyramid to extract amplify abnormal clues continuous frames, respectively. A lightweight sample labeling method based on landmarks is designed label large-scale samples at lower cost better results than other methods such as 3D camera. Finally, collect 30,000 live spoofing using various mobile ends create dataset that replicates forms of attacks real-world setting. Extensive experiments public OULU-NPU show our algorithm superior state art solution already been deployed systems servicing millions users.
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ژورنال
عنوان ژورنال: Proceedings
سال: 2022
ISSN: ['0890-1740']
DOI: https://doi.org/10.18293/seke2022-076