RiDDLE: Reversible and Diversified De-identification with Latent Encryptor

• URL: http://arxiv.org/abs/2303.05171v3
• Date: Sun, 23 Apr 2023 06:52:20 GMT
• Title: RiDDLE: Reversible and Diversified De-identification with Latent Encryptor
• Authors: Dongze Li, Wei Wang, Kang Zhao, Jing Dong and Tieniu Tan
• Abstract summary: This work presents RiDDLE, short for Reversible and Diversified De-identification with Latent Encryptor. Built upon a pre-learned StyleGAN2 generator, RiDDLE manages to encrypt and decrypt the facial identity within the latent space.
• Score: 57.66174700276893
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This work presents RiDDLE, short for Reversible and Diversified De-identification with Latent Encryptor, to protect the identity information of people from being misused. Built upon a pre-learned StyleGAN2 generator, RiDDLE manages to encrypt and decrypt the facial identity within the latent space. The design of RiDDLE has three appealing properties. First, the encryption process is cipher-guided and hence allows diverse anonymization using different passwords. Second, the true identity can only be decrypted with the correct password, otherwise the system will produce another de-identified face to maintain the privacy. Third, both encryption and decryption share an efficient implementation, benefiting from a carefully tailored lightweight encryptor. Comparisons with existing alternatives confirm that our approach accomplishes the de-identification task with better quality, higher diversity, and stronger reversibility. We further demonstrate the effectiveness of RiDDLE in anonymizing videos. Code and models will be made publicly available.

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