Face Recognition is considered one of the most common biometric solutions these days and
is widely used across a range of devices for various security purposes. The performance of …

With diverse presentation attacks emerging continually, generalizable face anti-spoofing
(FAS) has drawn growing attention. Most existing methods implement domain generalization …

This work studies the generalization issue of face anti-spoofing (FAS) models on domain
gaps, such as image resolution, blurriness and sensor variations. Most prior works regard …

Face anti-spoofing (FAS) has lately attracted increasing attention due to its vital role in
securing face recognition systems from presentation attacks (PAs). As more and more …

Biometrics has been evolving as an exciting yet challenging area in the last decade. Though
face recognition is one of the most promising biometrics techniques, it is vulnerable to …

The availability of handy multi-modal (ie, RGB-D) sensors has brought about a surge of face
anti-spoofing research. However, the current multi-modal face presentation attack detection …

Face anti-spoofing (FAS) or presentation attack detection is an essential component of face
recognition systems deployed in security-critical applications. Existing FAS methods have …

Face anti-spoofing (FAS) approaches based on unsupervised domain adaption (UDA) have
drawn growing attention due to promising performances for target scenarios. Most existing …

Abstract Domain generalization (DG) based Face Anti-Spoofing (FAS) aims to improve the
model's performance on unseen domains. Existing methods either rely on domain labels to …

Transferable adversarial attacks against Deep neural networks (DNNs) have received broad
attention in recent years. An adversarial example can be crafted by a surrogate model and …