16 citations · 18 across the 4 of their papers we have counts for
4 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…
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…
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…