26 citations · 26 across the 4 of their papers we have counts for
6 papers
Suppressing Gradient Conflict for Generalizable Deepfake Detection
Ming-Hui Liu, Harry Cheng, Xin Luo +1
Robust deepfake detection models must be capable of generalizing to ever-evolving manipulation techniques beyond training data. A promising strategy is to augment the training data…
Fair Deepfake Detectors Can Generalize
Harry Cheng, Ming-Hui Liu, Yangyang Guo +3
Deepfake detection models face two critical challenges: generalization to unseen manipulations and demographic fairness among population groups. However, existing approaches often…
Learning Real Facial Concepts for Independent Deepfake Detection
Ming-Hui Liu, Harry Cheng, Tianyi Wang +2
Deepfake detection models often struggle with generalization to unseen datasets, manifesting as misclassifying real instances as fake in target domains. This is primarily due to an…
FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarks
Tianyi Wang, Harry Cheng, Ming-Hui Liu +1
Proactive Deepfake detection via robust watermarks has seen interest ever since passive Deepfake detectors encountered challenges in identifying high-quality synthetic images. Howe…
NullSwap: Proactive Identity Cloaking Against Deepfake Face Swapping
Tianyi Wang, Harry Cheng, Xiao Zhang +1
Suffering from performance bottlenecks in passively detecting high-quality Deepfake images due to the advancement of generative models, proactive perturbations offer a promising ap…
LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarks
Tianyi Wang, Mengxiao Huang, Harry Cheng +2
Deepfake facial manipulation has garnered significant public attention due to its impacts on enhancing human experiences and posing privacy threats. Despite numerous passive algori…