6 papers · 1 filter
Detecting Deepfakes via Hamiltonian Dynamics
Harry Cheng, Ming-Hui Liu, Tianyi Wang +3
Driven by the rapid development of generative AI models, deepfake detectors are compelled to undergo periodic recalibration to capture newly developed synthetic artifacts. To break…
Towards Generalizable Deepfake Detection via Real Distribution Bias Correction
Ming-Hui Liu, Harry Cheng, Xin Luo +2
To generalize deepfake detectors to future unseen forgeries, most existing methods attempt to simulate the dynamically evolving forgery types using available source domain data. Ho…
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…
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…
DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attribution
Ming-Hui Liu, Xiao-Qian Liu, Xin Luo +1
Deepfake attribution (DFA) aims to perform multiclassification on different facial manipulation techniques, thereby mitigating the detrimental effects of forgery content on the soc…
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…