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cs.CV2024
A Quality-Centric Framework for Generic Deepfake Detection
Wentang Song, Zhiyuan Yan, Yuzhen Lin +6
Detecting AI-generated images, particularly deepfakes, has become increasingly crucial, with the primary challenge being the generalization to previously unseen manipulation method…
cs.CV2024
Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detection
Yuzhen Lin, Wentang Song, Bin Li +4
Previous studies in deepfake detection have shown promising results when testing face forgeries from the same dataset as the training. However, the problem remains challenging when…
cs.CV2024
FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge
Hanzhe Li, Jiaran Zhou, Yuezun Li +3
Generating synthetic fake faces, known as pseudo-fake faces, is an effective way to improve the generalization of DeepFake detection. Existing methods typically generate these face…