6 papers
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…
NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild
Aleksandr Gushchin, Khaled Abud, Ekaterina Shumitskaya +51
This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE workshop at CVPR 2026. The goal o…
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…
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…
GraphTEN: Graph Enhanced Texture Encoding Network
Bo Peng, Jintao Chen, Mufeng Yao +4
Texture recognition is a fundamental problem in computer vision and pattern recognition. Recent progress leverages feature aggregation into discriminative descriptions based on con…
MM-Tracker: Motion Mamba with Margin Loss for UAV-platform Multiple Object Tracking
Mufeng Yao, Jinlong Peng, Qingdong He +5
Multiple object tracking (MOT) from unmanned aerial vehicle (UAV) platforms requires efficient motion modeling. This is because UAV-MOT faces both local object motion and global ca…