5 papers
Simplicity Prevails: The Emergence of Generalizable AIGI Detection in Visual Foundation Models
Yue Zhou, Xinan He, Kaiqing Lin +3
While specialized detectors for AI-Generated Images (AIGI) achieve near-perfect accuracy on curated benchmarks, they suffer from a dramatic performance collapse in realistic, in-th…
MPF-Net: Exposing High-Fidelity AI-Generated Video Forgeries via Hierarchical Manifold Deviation and Micro-Temporal Fluctuations
Xinan He, Kaiqing Lin, Yue Zhou +8
With the rapid advancement of video generation models such as Veo and Wan, the visual quality of synthetic content has reached a level where macro-level semantic errors and tempora…
Brought a Gun to a Knife Fight: Modern VFM Baselines Outgun Specialized Detectors on In-the-Wild AI Image Detection
Yue Zhou, Xinan He, Kaiqing Lin +4
While specialized detectors for AI-generated images excel on curated benchmarks, they fail catastrophically in real-world scenarios, as evidenced by their critically high false-neg…
Breaking Latent Prior Bias in Detectors for Generalizable AIGC Image Detection
Yue Zhou, Xinan He, KaiQing Lin +3
Current AIGC detectors often achieve near-perfect accuracy on images produced by the same generator used for training but struggle to generalize to outputs from unseen generators.…
VLForgery Face Triad: Detection, Localization and Attribution via Multimodal Large Language Models
Xinan He, Yue Zhou, Bing Fan +3
Faces synthesized by diffusion models (DMs) with high-quality and controllable attributes pose a significant challenge for Deepfake detection. Most state-of-the-art detectors only…