collaborators

6 papers

cs.CV2026

ClueAegis: Heuristic-to-Reasoning Cognitive-skill Learning for Unified Evidence-based Synthetic Image Detection

Huangsen Cao, Hongkang Chu, Yuxi Li +6

The rapid advancement of generative models has made synthetic images increasingly realistic, challenging reliable detection. Existing methods are often limited to end-to-end classi…

cs.CV2026

Robust Deepfake Detection, NTIRE 2026 Challenge: Report

Benedikt Hopf, Radu Timofte, Chenfan Qu +54

Robustness is a long-overlooked problem in deepfake detection. However, detection performance is nearly worthless in the real world if it suffers under exposure to even slight imag…

cs.CV2026

REVEAL: Reasoning-Enhanced Forensic Evidence Analysis for Explainable AI-Generated Image Detection

Huangsen Cao, Qin Mei, Zhiheng Li +9

The rapid progress of visual generative models has made AI-generated images increasingly difficult to distinguish from authentic ones, posing growing risks to social trust and info…

cs.CV2026

LOGER: Local--Global Ensemble for Robust Deepfake Detection in the Wild

Fei Wu, Dagong Lu, Mufeng Yao +2

Robust deepfake detection in the wild remains challenging due to the ever-growing variety of manipulation techniques and uncontrolled real-world degradations. Forensic cues for dee…

cs.CV2026

HEDGE: Heterogeneous Ensemble for Detection of AI-GEnerated Images in the Wild

Fei Wu, Dagong Lu, Mufeng Yao +2

Robust detection of AI-generated images in the wild remains challenging due to the rapid evolution of generative models and varied real-world distortions. We argue that relying on…

cs.CV2026

Generalizable Detection of AI Generated Images with Large Models and Fuzzy Decision Tree

Fei Wu, Guanghao Ding, Zijian Niu +4

The malicious use and widespread dissemination of AI-generated images pose a serious threat to the authenticity of digital content. Existing detection methods exploit low-level art…