Fleet: Few Shots Lead Effective AI-generated Image Detection

arXiv:2606.31082v1 Announce Type: new Abstract: AI-generated image (AIGI) detection is undergoing a critical transition from laboratory benchmarks to open-world adversarial defense. The prevalent paradigm focuses on finding static feature spaces, assuming that some invariant artifacts learned from historical data can achieve universal zero-shot generalization. While achieving saturation on several AIGI benchmarks, this static hypothesis suffers a severe performance drop against rapidly evolving ...

arXiv cs.CV ·Jiaan Wang, Sirui Liu, Yu Li, Kaiyuan Yang, Juan Cao, Sheng Tang ·
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