From the 1 of 12 linked papers with an AI index.
12 papers
MotionPhys: Detecting AI-Generated Videos via Physical Consistency of Optical-Flow Trajectories
Haojin He, Hao Tan, Zichang Tan +2
Modern AI video generation models can produce videos with high visual fidelity and seemingly smooth temporal transitions. However, visual realism does not necessarily imply physica…
Unleashing the Potential of Vision-Language Models for Generalizable AI-Generated Image Detection
Weihan Cai, Hao Tan, Zichang Tan +2
Recent work has shown that a simple linear probe on frozen representations from modern vision foundation models (VFMs) can achieve state-of-the-art AIGI detection performance, subs…
Veritas++: Value-aware On-Policy Distillation for Perception-Enhanced AIGI Detection
Hao Tan, Jun Lan, Zichang Tan +7
Veritas++ introduces a perception‑enhanced framework for detecting AI‑generated images by training models to capture fine‑grained visual details, semantic anomalies, and pixel‑leve…
CTForensics: A Comprehensive Dataset and Method for AI-Generated CT Image Detection
Yiheng Li, Zichang Tan, Guoqing Xu +3
Recent advances in generative AI have made synthetic Computed Tomography (CT) images increasingly realistic, enabling promising applications in medical data augmentation while rais…
HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection
Senyuan Shi, Hao Tan, Zichang Tan +4
The rapid evolution of generative models has precipitated a proliferation of fabricated content, posing significant challenges to existing Synthetic Image Detection (SID) methods.…
Reduce the Artifacts Bias for More Generalizable AI-Generated Image Detection
Yiheng Li, Yang Yang, Zichang Tan +5
As the misuse of AI-generated images grows, generalizable image detection techniques are urgently needed. Recent state-of-the-art (SOTA) methods adopt aligned training datasets to…