1 citations · 3 across the 17 of their papers we have counts for
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MGFFD-VLM: Multi-Granularity Prompt Learning for Face Forgery Detection with VLM
Tao Chen, Jingyi Zhang, Decheng Liu +1
Recent studies have utilized visual large language models (VLMs) to answer not only "Is this face a forgery?" but also "Why is the face a forgery?" These studies introduced forgery…
A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation
Dawei Zhou, Suzhi Gang, Decheng Liu +3
Malicious applications of visual manipulation have raised serious threats to the security and reputation of users in many fields. To alleviate these issues, adversarial noise-based…
Towards Generalized Proactive Defense against Face Swapping with Contour-Hybrid Watermark
Ruiyang Xia, Dawei Zhou, Decheng Liu +4
Face swapping, recognized as a privacy and security concern, has prompted considerable defensive research. With the advancements in AI-generated content, the discrepancies between…
Improving Adversarial Robustness via Phase and Amplitude-aware Prompting
Yibo Xu, Dawei Zhou, Decheng Liu +1
Deep neural networks are found to be vulnerable to adversarial perturbations. The prompt-based defense has been increasingly studied due to its high efficiency. However, existing p…