Xiangyu Yu — accepted AI-conference papers

2026

ReAlign: Generalizable Image Forgery Detection via Reasoning-Aligned Representation

Qing Huang, Zhipei Xu, Xuanyu Zhang, Xiangyu Yu, Jian Zhang

CVPR 2026

The rise of AI-generated images (AIGIs) poses growing challenges for digital authenticity, prompting the need for efficient, generalizable image forgery detection systems. Existing methods, whether non-LLM-based or LLM-based, exhibit distinct advantages and limitations. While non-LLM-based models of

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2026

RecoverMark: Robust Watermarking for Localization and Recovery of Manipulated Faces

Haonan An, Xiaohui Ye, Guang Hua, Yihang Tao, Hangcheng Cao, Xiangyu Yu +1

CVPR 2026

The proliferation of AI-generated content (AIGC) has facilitated sophisticated face manipulation, severely undermining visual integrity and posing unprecedented challenges to intellectual property (IP). In response, a common proactive defense leverages fragile watermarks to detect, localize, or even

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