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Personalized and Invertible Face De-identification

  • Yunqian Wen,
  • Bo Liu,
  • Li Song,
  • Jingyi Cao,
  • Rong Xie

摘要

Most of the existing de-identification methods suffer from some limitations since they mainly focus on the protection process and are usually non-reversible. In this chapter, we propose a personalized and invertible de-identification method based on the deep generative model, where the main idea is to introduce a user-specific password and an adjustable parameter to control the direction and degree of identity variation.