Face anti-spoofing detection is critical to guarantee the security of biometric face recognition
systems. Despite extensive advances in facial anti-spoofing based on single-model image …

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems. Recently,
central difference convolution (CDC) has shown its excellent representation capacity for the …

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 detection is a crucial procedure in biometric face recognition systems.
State-of-the-art approaches, based on Convolutional Neural Networks (CNNs), present …

Although previous CNN based face anti-spoofing methods have achieved promising
performance under intra-dataset testing, they suffer from poor generalization under cross …

Regardless of the usage of deep learning and handcrafted methods, the dynamic
information from videos and the effect of cross-ethnicity are rarely considered in face anti …

Deep features extracted from different domains have shown great advantages in the face
anti-spoofing task. Previous extraction strategies consider less of the extent variation in …

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 …

One primary challenge in face anti-spoofing refers to suffering a sharp performance drop in
cross-domain scenes, where training and testing images are collected from different …

The emergence of biometric-based authentication using modern sensors on electronic
devices has led to an escalated use of face recognition technologies. While these …