March 8, 2024, 5:45 a.m. | Nan Zhong, Yiran Xu, Sheng Li, Zhenxing Qian, Xinpeng Zhang

cs.CV updates on arXiv.org arxiv.org

arXiv:2311.12397v3 Announce Type: replace
Abstract: Recent generative models show impressive performance in generating photographic images. Humans can hardly distinguish such incredibly realistic-looking AI-generated images from real ones. AI-generated images may lead to ubiquitous disinformation dissemination. Therefore, it is of utmost urgency to develop a detector to identify AI generated images. Most existing detectors suffer from sharp performance drops over unseen generative models. In this paper, we propose a novel AI-generated image detector capable of identifying fake images created by a …

abstract ai generated ai-generated image ai-generated images arxiv cs.cv detection disinformation generated generative generative models humans identify image image detection images performance show texture type

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