Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection

TL;DR

This paper introduces an identity hider that significantly alters facial appearance to protect human vision privacy while still allowing face recognition, using a novel virtual face generation and appearance transfer approach.

Contribution

It proposes a new method combining StyleGAN2-based virtual face generation and attribute transfer to enhance privacy protection without losing recognition capability.

Findings

Effective privacy protection demonstrated in experiments

High preservation of identity information for recognition

Supports diversity and background preservation

Abstract

Massive captured face images are stored in the database for the identification of individuals. However, these images can be observed unintentionally by data managers, which is not at the will of individuals and may cause privacy violations. Existing protection schemes can maintain identifiability but slightly change the facial appearance, rendering it still susceptible to the visual perception of the original identity by data managers. In this paper, we propose an effective identity hider for human vision protection, which can significantly change appearance to visually hide identity while allowing identification for face recognizers. Concretely, the identity hider benefits from two specially designed modules: 1) The virtual face generation module generates a virtual face with a new appearance by manipulating the latent space of StyleGAN2. In particular, the virtual face has a similar parsing map to the original face, supporting other vision tasks such as head pose detection. 2) The appearance transfer module transfers the appearance of the virtual face into the original face via attribute replacement. Meanwhile, identity information can be preserved well with the help of the disentanglement networks. In addition, diversity and background preservation are supported to meet the various requirements. Extensive experiments demonstrate that the proposed identity hider achieves excellent performance on privacy protection and identifiability preservation.