5 papers
Unleashing Vision-Language Semantics for Deepfake Video Detection
Jiawen Zhu, Yunqi Miao, Xueyi Zhang +2
Recent Deepfake Video Detection (DFD) studies have demonstrated that pre-trained Vision-Language Models (VLMs) such as CLIP exhibit strong generalization capabilities in detecting…
Interact2Ar: Full-Body Human-Human Interaction Generation via Autoregressive Diffusion Models
Pablo Ruiz-Ponce, Sergio Escalera, José García-Rodríguez +2
Generating realistic human-human interactions is a challenging task that requires not only high-quality individual body and hand motions, but also coherent coordination among all i…
Unified Physical-Digital Attack Detection Challenge
Haocheng Yuan, Ajian Liu, Junze Zheng +6
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, existin…
CFPL-FAS: Class Free Prompt Learning for Generalizable Face Anti-spoofing
Ajian Liu, Shuai Xue, Jianwen Gan +5
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 align domain-i…
Unified Physical-Digital Face Attack Detection
Hao Fang, Ajian Liu, Haocheng Yuan +8
Face Recognition (FR) systems can suffer from physical (i.e., print photo) and digital (i.e., DeepFake) attacks. However, previous related work rarely considers both situations at…