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 …

Face anti-spoofing is significant to the security of face recognition systems. Previous works
on depth supervised learning have proved the effectiveness for face anti-spoofing …

Face anti-spoofing (FAS) plays a vital role in preventing face recognition systems from
presentation attacks. Existing face anti-spoofing datasets lack diversity due to the insufficient …

Face anti-spoofing is an important task in full-stack face applications including face
detection, verification, and recognition. Previous approaches build models on datasets …

Face Anti-spoofing gains increased attentions recently in both academic and industrial
fields. With the emergence of various CNN based solutions, the multi-modal (RGB, depth …

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 benchmark …

Face anti-spoofing is essential to the face recognition system. Although previous work has
made great progress in spatial auxiliary supervision and temporal feature extraction, there …

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 weak …

In this paper, we propose a novel framework leveraging the advantages of the
representational ability of deep learning and domain generalization for face spoofing …

Face anti-spoofing is an important task to assure the security of face recognition systems. To
be applicable to unconstrained real-world environments, generalization capabilities of the …