1 citations · 2 across the 4 of their papers we have counts for
4 papers
Counterfactual Explanations for Face Forgery Detection via Adversarial Removal of Artifacts
Yang Li, Songlin Yang, Wei Wang +3
Highly realistic AI generated face forgeries known as deepfakes have raised serious social concerns. Although DNN-based face forgery detection models have achieved good performance…
Is It Possible to Backdoor Face Forgery Detection with Natural Triggers?
Xiaoxuan Han, Songlin Yang, Wei Wang +2
Deep neural networks have significantly improved the performance of face forgery detection models in discriminating Artificial Intelligent Generated Content (AIGC). However, their…
3D-Aware Adversarial Makeup Generation for Facial Privacy Protection
Yueming Lyu, Yue Jiang, Ziwen He +3
The privacy and security of face data on social media are facing unprecedented challenges as it is vulnerable to unauthorized access and identification. A common practice for solvi…
Exposing Fine-Grained Adversarial Vulnerability of Face Anti-Spoofing Models
Songlin Yang, Wei Wang, Chenye Xu +3
Face anti-spoofing aims to discriminate the spoofing face images (e.g., printed photos) from live ones. However, adversarial examples greatly challenge its credibility, where addin…