Eye gaze analysis is an important research problem in the field of Computer Vision and
Human-Computer Interaction. Even with notable progress in the last 10 years, automatic …

Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …

During COVID-19 coronavirus epidemic, almost everyone wears a mask to prevent the
spread of virus. It raises a problem that the traditional face recognition model basically fails …

This paper proposes a self-supervised approach to learn universal facial representations
from videos, that can transfer across a variety of facial analysis tasks such as Facial Attribute …

The emergence of COVID-19 has had a global and profound impact, not only on society as a
whole, but also on the lives of individuals. Various prevention measures were introduced …

During the COVID-19 coronavirus epidemic, almost everyone wears a facial mask, which
poses a huge challenge to deep face recognition. In this workshop, we organize Masked …

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

With the recent advancement of deep convolutional neural networks, significant progress
has been made in general face recognition. However, the state-of-the-art general face …

Face presentation attack detection (PAD) is essential to secure face recognition systems
primarily from high-fidelity mask attacks. Most existing 3D mask PAD benchmarks suffer from …

Abstract Face Anti-Spoofing (FAS) is pivotal in safeguarding facial recognition systems
against presentation attacks. While domain generalization (DG) methods have been …