2 citations · 3 across the 17 of their papers we have counts for
16 papers · 1 filter
CIEC: Coupling Implicit and Explicit Cues for Multimodal Weakly Supervised Manipulation Localization
Xinquan Yu, Wei Lu, Xiangyang Luo +1
To mitigate the threat of misinformation, multimodal manipulation localization has garnered growing attention. Consider that current methods rely on costly and time-consuming fine-…
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…
Safeguarding Facial Identity against Diffusion-based Face Swapping via Cascading Pathway Disruption
Liqin Wang, Qianyue Hu, Wei Lu +1
The rapid evolution of diffusion models has democratized face swapping but also raises concerns about privacy and identity security. Existing proactive defenses, often adapted from…
Fine-grained Multiple Supervisory Network for Multi-modal Manipulation Detecting and Grounding
Xinquan Yu, Wei Lu, Xiangyang Luo
The task of Detecting and Grounding Multi-Modal Media Manipulation (DGM) is a branch of misinformation detection. Unlike traditional binary classification, it includes complex…
Weakly Supervised Multimodal Temporal Forgery Localization via Multitask Learning
Wenbo Xu, Wei Lu, Xiangyang Luo
The spread of Deepfake videos has caused a trust crisis and impaired social stability. Although numerous approaches have been proposed to address the challenges of Deepfake detecti…
A Multimodal Deviation Perceiving Framework for Weakly-Supervised Temporal Forgery Localization
Wenbo Xu, Junyan Wu, Wei Lu +2
Current researches on Deepfake forensics often treat detection as a classification task or temporal forgery localization problem, which are usually restrictive, time-consuming, and…