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InfoResearchPeer-reviewed
Identifiable Face to Face for Privacy Protection
- Published
- Record updated
Summary
The authors propose IF2F, a face anonymization scheme that transforms an original face image into an identifiable, anonymized "self-transformed" face, built on a pretrained StyleGAN inversion encoder and generator. It uses a robust face hashing (RFH) module and a multi-scale conditional latent transformer (MCLT), trained with an auxiliary feature bank strategy and loss functions for anonymity, identifiability and visual quality. Experiments reportedly show it outperforms existing face privacy protection schemes.