16 citations · 19 across the 20 of their papers we have counts for
10 papers · 1 filter
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…
Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization
Qilin Yin, Wei Lu, Xiangyang Luo +1
Most research efforts in the multimedia forensics domain have focused on detecting forgery audio-visual content and reached sound achievements. However, these works only consider d…
ARIW-Framework: Adaptive Robust Iterative Watermarking Framework
Shaowu Wu, Liting Zeng, Wei Lu +1
With the rapid rise of large models, copyright protection for generated image content has become a critical security challenge. Although deep learning watermarking techniques offer…
Towards Open-world Generalized Deepfake Detection: General Feature Extraction via Unsupervised Domain Adaptation
Midou Guo, Qilin Yin, Wei Lu +1
With the development of generative artificial intelligence, new forgery methods are rapidly emerging. Social platforms are flooded with vast amounts of unlabeled synthetic data and…
Weakly-supervised Audio Temporal Forgery Localization via Progressive Audio-language Co-learning Network
Junyan Wu, Wenbo Xu, Wei Lu +3
Audio temporal forgery localization (ATFL) aims to find the precise forgery regions of the partial spoof audio that is purposefully modified. Existing ATFL methods rely on training…
Anti-Inpainting: A Proactive Defense Approach against Malicious Diffusion-based Inpainters under Unknown Conditions
Yimao Guo, Zuomin Qu, Wei Lu +1
With the increasing prevalence of diffusion-based malicious image manipulation, existing proactive defense methods struggle to safeguard images against tampering under unknown cond…
VoiceCloak: A Multi-Dimensional Defense Framework against Unauthorized Diffusion-based Voice Cloning
Qianyue Hu, Junyan Wu, Wei Lu +1
Diffusion Models (DMs) have achieved remarkable success in realistic voice cloning (VC), while they also increase the risk of malicious misuse. Existing proactive defenses designed…
Diffusion-based Adversarial Identity Manipulation for Facial Privacy Protection
Liqin Wang, Qianyue Hu, Wei Lu +1
The success of face recognition (FR) systems has led to serious privacy concerns due to potential unauthorized surveillance and user tracking on social networks. Existing methods f…