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arXiv Computer Vision By Xin Jiang, Hao Tang, Junyao Gao, Meiqi Cao, Fei Shen, Dongming Zhang, Yongdong Zhang

DailyBench: A Unified Benchmark for AI-Generated and Manipulated Images from Modern Generative Models

Read the original on arXiv Computer Vision →

DailyBench is a unified benchmark designed to evaluate AI-generated image detectors on both modern full-image synthesis and object-level manipulation. It comprises two subsets: FakeBench, featuring high‑quality images from recent open‑source and commercial generative models, and ManipulationBench, containing subtle local edits applied to real images using advanced image‑conditional models. Experiments show that detectors with high accuracy on older datasets perform poorly on DailyBench, revealing significant robustness gaps.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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