mlsanityData to 13 Oct 2026

UniAIDet: A Unified and Universal Benchmark for AI-Generated Image Content Detection and Localization

arXiv 2510.23023 ↗First posted 27 Oct 2025cs.CV cs.CLcited by 1

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Abstract (arXiv)

With the rapid proliferation of image generative models, the authenticity of digital images has become a significant concern. While existing studies have proposed various methods for detecting AI-generated content, current benchmarks are limited in their coverage of diverse generative models and image categories, often overlooking end-to-end image editing and artistic images. To address these limitations, we introduce UniAIDet, a unified and comprehensive benchmark that includes both photographic and artistic images. UniAIDet covers a wide range of generative models, including text-to-image, image-to-image, image inpainting, image editing, and deepfake models. Using UniAIDet, we conduct a comprehensive evaluation of various detection methods and answer three key research questions regarding generalization capability and the relation between detection and localization. Our benchmark and analysis provide a robust foundation for future research.

Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 37 of its 48 references that are in the map. First posted on arXiv 27 Oct 2025.

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37 of 48 references.

References · 37

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25 more
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