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cs.CV2026

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection

Haoyu Wang, Yiming Qin, Zhongjie Ba +4

AI-generated images have proliferated rapidly, motivating extensive research. Most existing AI-generated image detectors are developed and evaluated under image-free generation par…

cs.CV2026

When Detectors Forget Forensics: Blocking Semantic Shortcuts for Generalizable AI-Generated Image Detection

Chao Shuai, Shaojing Fan, Chenlin Zou +6

The growing realism of generative models has blurred the boundary between real and synthetic content, posing significant challenges to reliable AI-generated image detection. Althou…

cs.CV2025

Scalable Face Security Vision Foundation Model for Deepfake, Diffusion, and Spoofing Detection

Gaojian Wang, Feng Lin, Tong Wu +2

With abundant, unlabeled real faces, how can we learn robust and transferable facial representations to boost generalization across various face security tasks? We make the first a…

cs.CV2025

Morphology-optimized Multi-Scale Fusion: Combining Local Artifacts and Mesoscopic Semantics for Deepfake Detection and Localization

Chao Shuai, Gaojian Wang, Kun Pan +7

While the pursuit of higher accuracy in deepfake detection remains a central goal, there is an increasing demand for precise localization of manipulated regions. Despite the remark…

cs.CV2025

Robust Representation Consistency Model via Contrastive Denoising

Jiachen Lei, Julius Berner, Jiongxiao Wang +5

Robustness is essential for deep neural networks, especially in security-sensitive applications. To this end, randomized smoothing provides theoretical guarantees for certifying ro…

cs.CV2025

FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning

Gaojian Wang, Feng Lin, Tong Wu +3

This work asks: with abundant, unlabeled real faces, how to learn a robust and transferable facial representation that boosts various face security tasks with respect to generaliza…