2025
Data-free Universal Adversarial Perturbation with Pseudo-semantic Prior
CVPR 2025poster
Data-free Universal Adversarial Perturbation (UAP) is an image-agnostic adversarial attack that deceives deep neural networks using a single perturbation generated solely from random noise without relying on data priors. However, traditional data-free UAP methods often suffer from limited transferab…