Enhancing Facial Privacy Protection via Weakening Diffusion Purification

Noise-based Makeup-based Diffusion-based 48.38 38.58 * indicates the corresponding author human observers to recognize the generated image as having the same identity as the original. Extensive experiments conducted on two public datasets, i.e., CelebA-HQ and LADN, demonstrate the superiority of our approach. The protected faces generated by our method outperform those produced by existing facial privacy protection approaches