5 papers
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…
Seeing Before Reasoning: A Unified Framework for Generalizable and Explainable Fake Image Detection
Kaiqing Lin, Zhiyuan Yan, Ruoxin Chen +7
Detecting AI-generated images with multimodal large language models (MLLMs) has gained increasing attention, due to their rich world knowledge, common-sense reasoning, and potentia…
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.…
Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakes
Kaiqing Lin, Zhiyuan Yan, Ke-Yue Zhang +7
Securing personal identity against deepfake attacks is increasingly critical in the digital age, especially for celebrities and political figures whose faces are easily accessible…