Mirage-Test is a modern test-only dataset for benchmarking AI-generated image detection models.
It contains real (0_real) and fake (1_fake) images across five distinct content domains, designed to evaluate generalization across diverse visual semantics.
The fake images are generated using state-of-the-art generative models specifically optimized for perceptual realism and visual fidelity.