computer vision

A one-class detector trained only on real images, scoring how atypical an image is in feature space. The hypothesis was that it would generalise to unseen generators better than a discriminative classifier. It did not: the baseline won, including on the held-out generator. A negative result cleanly obtained, with a distributional explanation.

Work

A compact CNN classifying images as real or AI-generated, trained on Defactify across five generators, small enough at 1.7 MB to run on CPU. The part that matters is the holdout experiment: train with one generator withheld, then report per-generator recall, so the number is transfer rather than memorisation.

Work