45 citations · 71 across the 14 of their papers we have counts for
14 papers
Towards General Visual-Linguistic Face Forgery Detection(V2)
Ke Sun, Shen Chen, Taiping Yao +5
Face manipulation techniques have achieved significant advances, presenting serious challenges to security and social trust. Recent works demonstrate that leveraging multimodal mod…
DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion
Ke Sun, Shen Chen, Taiping Yao +4
The rapid progress of Deepfake technology has made face swapping highly realistic, raising concerns about the malicious use of fabricated facial content. Existing methods often str…
Contrastive Pseudo Learning for Open-World DeepFake Attribution
Zhimin Sun, Shen Chen, Taiping Yao +4
The challenge in sourcing attribution for forgery faces has gained widespread attention due to the rapid development of generative techniques. While many recent works have taken es…
Continual Face Forgery Detection via Historical Distribution Preserving
Ke Sun, Shen Chen, Taiping Yao +3
Face forgery techniques have advanced rapidly and pose serious security threats. Existing face forgery detection methods try to learn generalizable features, but they still fall sh…
Towards General Visual-Linguistic Face Forgery Detection
Ke Sun, Shen Chen, Taiping Yao +4
Deepfakes are realistic face manipulations that can pose serious threats to security, privacy, and trust. Existing methods mostly treat this task as binary classification, which us…
Cheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
Gen Luo, Yiyi Zhou, Tianhe Ren +3
Recently, growing interest has been aroused in extending the multimodal capability of large language models (LLMs), e.g., vision-language (VL) learning, which is regarded as the ne…