Face anti-spoofing is crucial to security of face recognition systems. Previous approaches
focus on developing discriminative models based on the features extracted from images …

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 …

Inspired by the philosophy employed by human beings to determine whether a presented
face example is genuine or not, ie, to glance at the example globally first and then carefully …

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

Nowadays, the increasingly growing number of mobile and computing devices has led to a
demand for safer user authentication systems. Face anti-spoofing is a measure towards this …

Prior studies show that the key to face anti-spoofing lies in the subtle image patterns, termed
“spoof trace,” eg, color distortion, 3D mask edge, and Moiré pattern. Spoof detection rooted …

Face anti-spoofing is crucial to prevent face recognition systems from a security breach.
Previous deep learning approaches formulate face anti-spoofing as a binary classification …

Face anti-spoofing (FAS) plays a critical role in securing face recognition systems from
different presentation attacks. Previous works leverage auxiliary pixel-level supervision and …

As facial interaction systems are prevalently deployed, security and reliability of these
systems become a critical issue, with substantial research efforts devoted. Among them, face …

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 …