Adversarial Facial Obfuscation against Unauthorized Face Recognition
Jingbo Hao, Yang Tao · Journal of Physics Conference Series · 2021
Abstract To protect individual privacy from unauthorized face recognition based on DNN models, adversarial facial obfuscation tries to generate an adversarial image with a feature vector differing markedly from the original image in the embedding space and keep perceptually similar between the two images simultaneously. This paper makes a brief survey of adversarial facial obfuscation. The preliminary theory about facial obfuscation is introduced first. With regard to adversarial facial obfuscation, the most important implementation factors consisting of transferability, perceptibility and compression resistance are also presented.