The vulnerability of face recognition systems to presentation attacks (also known as direct
attacks or spoof attacks) has received a great deal of interest from the biometric community …

Machine learning (ML) is widely used for key tasks in Connected and Automated Vehicles
(CAV), including perception, planning, and control. However, its reliance on vehicular data …

Face anti-spoofing (FAS) plays a vital role in face recognition systems. Most state-of-the-art
FAS methods 1) rely on stacked convolutions and expert-designed network, which is weak …

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 …

Face anti-spoofing (FAS) plays a vital role in securing face recognition systems. Existing
methods heavily rely on the expert-designed networks, which may lead to a sub-optimal …

The new developments in deep generative networks have significantly improve the quality
and efficiency in generating realistically-looking fake face videos. In this work, we describe a …

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 …

Existing domain generalization methods for face anti-spoofing endeavor to extract common
differentiation features to improve the generalization. However, due to large distribution …

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 …