Personalized and Invertible Face De-identification by Disentangled Identity Information Manipulation

Author:

Cao Jingyi1,Liu Bo2,Wen Yunqian1,Xie Rong1,Song Li1

Affiliation:

1. Shanghai Jiao Tong University,The Institute of Image Communication and Network Engineering

2. University of Technology Sydney,School of Computer Science

Publisher

IEEE

Reference27 articles.

1. DeepPrivacy: A Generative Adversarial Network for Face Anonymization

2. Progressive growing of GANs for improved quality, stability, and variation;karras;International Conference on Learning Representations,2018

3. A Style-Based Generator Architecture for Generative Adversarial Networks

4. Faceshifter: Towards high fidelity and occlusion aware face swapping;li,2019

5. SphereFace: Deep Hypersphere Embedding for Face Recognition

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3. Data-Driven but Privacy-Conscious: Pedestrian Dataset De-Identification via Full-Body Person Synthesis;2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG);2024-05-27

4. Multi-channel attribute preservation for face de-identification;Multimedia Tools and Applications;2024-05-24

5. Manipulable, reversible and diversified de-identification via face identity disentanglement;Multimedia Tools and Applications;2024-02-19

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