Chengyang Hu — accepted AI-conference papers

2024

Domain-Hallucinated Updating for Multi-Domain Face Anti-spoofing

Chengyang Hu, Ke-Yue Zhang, Taiping Yao, Shice Liu, Shouhong Ding, Xin Tan +1

AAAI 2024technical

Multi-Domain Face Anti-Spoofing (MD-FAS) is a practical setting that aims to update models on new domains using only novel data while ensuring that the knowledge acquired from previous domains is not forgotten. Prior methods utilize the responses from models to represent the previous domain knowledg…

Cited by 3 Source ↗PDF ↗Scholar ↗

2024

Rethinking Generalizable Face Anti-spoofing via Hierarchical Prototype-guided Distribution Refinement in Hyperbolic Space

Chengyang Hu, Ke-Yue Zhang, Taiping Yao, Shouhong Ding, Lizhuang Ma

CVPR 2024highlight

Generalizable face anti-spoofing (FAS) approaches have drawn growing attention due to their robustness for diverse presentation attacks in unseen scenarios. Most previous methods always utilize domain generalization (DG) frameworks via directly aligning diverse source samples into a common feature s…

Cited by 12 Source ↗PDF ↗Scholar ↗