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…
DIP: Diffusion Learning of Inconsistency Pattern for General DeepFake Detection
Fan Nie, Jiangqun Ni, Jian Zhang +2
With the advancement of deepfake generation techniques, the importance of deepfake detection in protecting multimedia content integrity has become increasingly obvious. Recently, t…