NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild
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 of this challenge was to develop detection models capable of distinguishing real images from generated ones in realistic scenarios: the images are often transformed (cropped, resized, compressed, blurred) for practical usage, and therefore, the detection models should be robust to such transformations. The challenge is based on a novel dataset consisting of 108,750 real and 185,750 AI-generated images from 42 generators comprising a large variety of open-source and closed-source models of various architectures, a...
| Authors | Aleksandr Gushchin, Khaled Abud, Ekaterina Shumitskaya et al. |
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| Primary category | cs.CV |
| Published | 13 April 2026 |
| Last updated at source | 13 April 2026 |
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