Over the last few years, the adoption of machine learning in a wide range of domains has
been remarkable. Deep learning, in particular, has been extensively used to drive …

The human face is considered the prime entity in recognizing a person's identity in our
society. Henceforth, the importance of face recognition systems is growing higher for many …

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

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 …

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 …

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 Presentation Attack Detection (PAD) approaches based on multi-modal data have
been attracted increasingly by the research community. However, they require multi-modal …

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 …

With the popularity of smartphones, we have witnessed the rapid proliferation of multimodal
posts on various social media platforms. We observe that the multimodal sentiment …

While recent face anti-spoofing methods perform well under the intra-domain setups, an
effective approach needs to account for much larger appearance variations of images …