Local features contain crucial clues for face anti-spoofing. Convolutional neural networks
(CNNs) are powerful in extracting local features, but the intrinsic inductive bias of CNNs …

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 …

Since the rapid development of face recognition systems using 3D cameras, the public has
demanded great safety regulations for these devices. As a closely related topic, multimodal …

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 …

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

Existing face anti-spoofing models using deep learning for multimodality data suffer from low
generalization in the case of using variety of presentation attacks, such as 2-D printing and …

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 …

The recent boom in publicly available face authentication (FA) system has brought forward
the susceptibility of FA systems to different attack vectors, especially spoofing/presentation …

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 …