3 papers
cs.CV2025
FaceShield: Explainable Face Anti-Spoofing with Multimodal Large Language Models
Hongyang Wang, Yichen Shi, Zhuofu Tao +7
Face anti-spoofing (FAS) is crucial for protecting facial recognition systems from presentation attacks. Previous methods approached this task as a classification problem, lacking…
cs.CV2025
DADM: Dual Alignment of Domain and Modality for Face Anti-spoofing
Jingyi Yang, Xun Lin, Zitong Yu +5
With the availability of diverse sensor modalities (i.e., RGB, Depth, Infrared) and the success of multi-modal learning, multi-modal face anti-spoofing (FAS) has emerged as a promi…
cs.CV2025
GVformer: Graph Guided Video Vision Transformer for Face Anti-Spoofing
Jingyi Yang, Zitong Yu, Xiuming Ni +2
In videos containing spoofed faces, we may uncover the spoofing evidence based on either photometric or dynamic abnormality, even a combination of both. Prevailing face anti-spoofi…