Biometric recognition refers to the automated recognition of individuals based on their
biological and behavioral characteristics such as fingerprint, face, iris, and voice. The first …

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 …

As realistic facial manipulation technologies have achieved remarkable progress, social
concerns about potential malicious abuse of these technologies bring out an emerging …

Face anti-spoofing (FAS) based on domain generalization (DG) has been recently studied to
improve the generalization on unseen scenarios. Previous methods typically rely on domain …

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 …

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 …

The face image is the most accessible biometric modality which is used for highly accurate
face recognition systems, while it is vulnerable to many different types of presentation …

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

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 …

Many prior face anti-spoofing works develop discriminative models for recognizing the
subtle differences between live and spoof faces. Those approaches often regard the image …