23 citations · 46 across the 3 of their papers we have counts for
8 papers
Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofing
Zhuo Wang, Zezheng Wang, Zitong Yu +4
With diverse presentation attacks emerging continually, generalizable face anti-spoofing (FAS) has drawn growing attention. Most existing methods implement domain generalization (D…
PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition
Qiang Meng, Xiaqing Xu, Xiaobo Wang +6
Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e.g.…
Multi-Modal Face Anti-Spoofing Based on Central Difference Networks
Zitong Yu, Yunxiao Qin, Xiaobai Li +4
Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from presentation attacks. Existing multi-modal FAS methods rely on stacked vanilla convolutions, w…
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
Zezheng Wang, Zitong Yu, Chenxu Zhao +5
Face anti-spoofing is critical to the security of face recognition systems. Depth supervised learning has been proven as one of the most effective methods for face anti-spoofing. D…
Searching Central Difference Convolutional Networks for Face Anti-Spoofing
Zitong Yu, Chenxu Zhao, Zezheng Wang +5
Face anti-spoofing (FAS) plays a vital role in face recognition systems. Most state-of-the-art FAS methods 1) rely on stacked convolutions and expert-designed network, which is wea…
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofing
Shifeng Zhang, Xiaobo Wang, Ajian Liu +6
Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmar…