4 papers
Towards Generalizable Deepfake Detection via Forgery-aware Audio-Visual Adaptation: A Variational Bayesian Approach
Fan Nie, Jiangqun Ni, Jian Zhang +3
The widespread application of AIGC contents has brought not only unprecedented opportunities, but also potential security concerns, e.g., audio-visual deepfakes. Therefore, it is o…
Toward Real-world Text Image Forgery Localization: Structured and Interpretable Data Synthesis
Zeqin Yu, Haotao Xie, Jian Zhang +3
Existing Text Image Forgery Localization (T-IFL) methods often suffer from poor generalization due to the limited scale of real-world datasets and the distribution gap caused by sy…
Reinforced Multi-teacher Knowledge Distillation for Efficient General Image Forgery Detection and Localization
Zeqin Yu, Jiangqun Ni, Jian Zhang +2
Image forgery detection and localization (IFDL) is of vital importance as forged images can spread misinformation that poses potential threats to our daily lives. However, previous…
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…