6 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.CV2024
-norm Distortion-Efficient Adversarial Attack
Chao Zhou, Yuan-Gen Wang, Zi-jia Wang +1
Adversarial examples have shown a powerful ability to make a well-trained model misclassified. Current mainstream adversarial attack methods only consider one of the distortions am…
cs.CV2024★ 6 cited
GM-DF: Generalized Multi-Scenario Deepfake Detection
Yingxin Lai, Zitong Yu, Jing Yang +3
Existing face forgery detection usually follows the paradigm of training models in a single domain, which leads to limited generalization capacity when unseen scenarios and unknown…
cs.CV2023★ 3 cited
Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detection
Anwei Luo, Chenqi Kong, Jiwu Huang +3
Face forgery detection is essential in combating malicious digital face attacks. Previous methods mainly rely on prior expert knowledge to capture specific forgery clues, such as n…