Low, High, and Semantic-Level Vision-Language Learning for AI-Generated Image Detection
Driven by advances in diffusion models and autoregressive models, the fidelity and resolution of AI-generated images now rival those of real images. However, existing AI-generated image detection methods often downsample the images,inevitably overlooking critical low-level texture details in high-resolution AI-generated images, thereby limiting their detection performance. In addition, the continuous emergence of unknown generative models makes large-scale pre-training datasets inaccessible. To address these challenges, we propose a novel AI-generated image detector, termed LHSDet (Low-, High-, and Semantic-level Detection). Specifically, we formulate the AI-generated image detection task...
| Authors | Qian Yao, Luming Yang, Jun-Jie Huang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 August 2026 |
| Last updated at source | 9 October 2026 |
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