5 papers
MARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models
Wenbo Xu, Wei Lu, Xiangyang Luo +1
Deepfake detection is a widely researched topic that is crucial for combating the spread of malicious content, with existing methods mainly modeling the problem as classification o…
Weakly-Supervised Image Forgery Localization via Vision-Language Collaborative Reasoning Framework
Ziqi Sheng, Junyan Wu, Wei Lu +1
Image forgery localization aims to precisely identify tampered regions within images, but it commonly depends on costly pixel-level annotations. To alleviate this annotation burden…
GLCF: A Global-Local Multimodal Coherence Analysis Framework for Talking Face Generation Detection
Xiaocan Chen, Qilin Yin, Jiarui Liu +3
Talking face generation (TFG) allows for producing lifelike talking videos of any character using only facial images and accompanying text. Abuse of this technology could pose sign…
SUMI-IFL: An Information-Theoretic Framework for Image Forgery Localization with Sufficiency and Minimality Constraints
Ziqi Sheng, Wei Lu, Xiangyang Luo +2
Image forgery localization (IFL) is a crucial technique for preventing tampered image misuse and protecting social safety. However, due to the rapid development of image tampering…
RaCMC: Residual-Aware Compensation Network with Multi-Granularity Constraints for Fake News Detection
Xinquan Yu, Ziqi Sheng, Wei Lu +2
Multimodal fake news detection aims to automatically identify real or fake news, thereby mitigating the adverse effects caused by such misinformation. Although prevailing approache…