Face anti-spoofing (FAS) plays a vital role in securing face recognition systems from the
presentation attacks (PAs). As more and more realistic PAs with novel types spring up, it is …

Abstract Face Anti-Spoofing (FAS) is crucial to safeguard Face Recognition (FR) Systems. In
real-world scenarios FRs are confronted with both physical and digital attacks. However …

Character Animation aims to generating character videos from still images through driving
signals. Currently diffusion models have become the mainstream in visual generation …

Single image dehazing is a challenging ill-posed problem which estimates latent haze-free
images from observed hazy images. Some existing deep learning based methods are …

Abstract Recently, deep Convolutional Neural Networks (CNNs) can achieve human-level
performance in edge detection with the rich and abstract edge representation capacities …

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

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 …

Existing methods of 3D dthus limiting the scope of their practical applications. In this paper,
we propose a novel regression framework which makes a balance among speed, accuracy …

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 …

While the significant advancements have made in the generation of deepfakes using deep
learning technologies, its misuse is a well-known issue now. Deepfakes can cause severe …