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cs.CV2026

Rethinking the Readout: Unlocking Video Backbones for AI-Generated Video Detection

Manni Cui, Ziheng Qin, ZiAn Wang +8

AI-generated videos (AIGVs) typically contain subtle temporal artifacts that arise from inter-frame inconsistencies rather than within individual frames. A detector that captures s…

cs.CV2026

GlobalForge: Towards Robust AI-Generated Image Detection

Manni Cui, Ruiqi Liu, Dianyuan Zou +8

AI-generated image (AIGI) detectors achieve strong accuracy on clean benchmarks, but their performance drops sharply after images are propagated through real-world channels. We tra…

cs.CV2026

MIRROR: Manifold Ideal Reference ReconstructOR for Generalizable AI-Generated Image Detection

Ruiqi Liu, Manni Cui, Ziheng Qin +12

High-fidelity generative models have narrowed the perceptual gap between synthetic and real images, posing serious threats to media security. Most existing AI-generated image (AIGI…

cs.CV2025

Beyond Artifacts: Real-Centric Envelope Modeling for Reliable AI-Generated Image Detection

Ruiqi Liu, Yi Han, Zhengbo Zhang +9

The rapid progress of generative models has intensified the need for reliable and robust detection under real-world conditions. However, existing detectors often overfit to generat…

cs.CV2025

DINO-Detect: A Simple yet Effective Framework for Blur-Robust AI-Generated Image Detection

Jialiang Shen, Jiyang Zheng, Yunqi Xue +8

With growing concerns over image authenticity and digital safety, the field of AI-generated image (AIGI) detection has progressed rapidly. Yet, most AIGI detectors still struggle u…