16 citations · 18 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
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…
Coarse-to-Fine Proposal Refinement Framework for Audio Temporal Forgery Detection and Localization
Junyan Wu, Wei Lu, Xiangyang Luo +3
Recently, a novel form of audio partial forgery has posed challenges to its forensics, requiring advanced countermeasures to detect subtle forgery manipulations within long-duratio…