Prior-Conditioned Gaussian Discriminants for Generalizable AI-generated Image Detection
Diffusion-based generators have made synthetic images ubiquitous, but detectors often fail under simultaneous shifts in generator, prompt/style, and source-domain. We study AI-generated image detection as a transfer system described by training prior, frozen encoder feature space, and decision rule, and ask when classifier head training adds value beyond what is already separable in modern features. As a controlled diagnostic, we fit a prior-conditioned Gaussian discriminant ladder: closed-form heads built from first- and second-order feature statistics under nested covariance assumptions. On Percept-Lens, a unified protocol over 39 public datasets (7.1 million images), the best rung is f...
| Authors | Shashank Kotyan, Makoto Shing, Yuki Imajuku et al. |
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| Primary category | cs.CV |
| Published | 19 August 2026 |
| Last updated at source | 19 August 2026 |
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