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cs.CV2026

Semantic Manipulation Localization

Zhenshan Tan, Chenhan Lu, Yuxiang Huang +6

Image Manipulation Localization (IML) aims to identify edited regions in an image. However, with the increasing use of modern image editing and generative models, many manipulation…

cs.CV2026

Low-rank Orthogonal Subspace Intervention for Generalizable Face Forgery Detection

Chi Wang, Xinjue Hu, Boyu Wang +2

The generalization problem remains a key challenge in face forgery detection. This paper explores the reasons for the generalization failure of Vanilla CLIP: in ``real vs. fake" de…

cs.CV2026

Generalizable Deepfake Detection Based on Forgery-aware Layer Masking and Multi-artifact Subspace Decomposition

Xiang Zhang, Wenliang Weng, Daoyong Fu +4

Deepfake detection remains highly challenging, particularly in cross-dataset scenarios and complex real-world settings. This challenge mainly arises because artifact patterns vary…

cs.CV2025

DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection

Jiazhen Yan, Ziqiang Li, Fan Wang +3

The rapid progress of generative models such as GANs and diffusion models has led to the widespread proliferation of AI-generated images, raising concerns about misinformation, pri…

cs.CV2025

Is Artificial Intelligence Generated Image Detection a Solved Problem?

Ziqiang Li, Jiazhen Yan, Ziwen He +4

The rapid advancement of generative models, such as GANs and Diffusion models, has enabled the creation of highly realistic synthetic images, raising serious concerns about misinfo…

cs.CV2025

Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detection

Jiazhen Yan, Ziqiang Li, Fan Wang +2

The rapid advancement of Generative Adversarial Networks (GANs) and diffusion models has enabled the creation of highly realistic synthetic images, presenting significant societal…