AI RESEARCH
A Mimetic Detector for Adversarial Image Perturbations
arXiv CS.CV
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ArXi:2605.11492v1 Announce Type: new Adversarial attacks fool deep image classifiers by adding tiny, almost invisible noise patterns to a clean image. The standard $\ell^\infty$-bounded attacks (FGSM, PGD, and the $\ell^\infty$ variant of Carlini--Wagner) produce high-frequency, near-random sign patterns at the pixel level: nearly invisible in $\ell^2$, but carrying disproportionate gradient energy. We exploit this with a single-shot