De-identification Without Losing Faces
Author:
Affiliation:
1. University at Albany, State University of New York, Albany, NY, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3335203.3335719
Reference26 articles.
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4. Integrating Utility into Face De-identification
5. Ralph Gross Latanya Sweeney Jeffrey Cohn Fernando De la Torre and Simon Baker. 2009. Face de-identification. In Protecting privacy in video surveillance . Ralph Gross Latanya Sweeney Jeffrey Cohn Fernando De la Torre and Simon Baker. 2009. Face de-identification. In Protecting privacy in video surveillance .
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1. Privacy-Protected Facial Expression Recognition Augmented by High-Resolution Facial Images;2023 IEEE International Conference on Multimedia and Expo (ICME);2023-07
2. Private Image Generation with Dual-Purpose Auxiliary Classifier;2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2023-06
3. IdentityMask: Deep Motion Flow Guided Reversible Face Video De-Identification;IEEE Transactions on Circuits and Systems for Video Technology;2022-12
4. Fairness and privacy preservation for facial images: GAN-based methods;Computers & Security;2022-11
5. Protecting the Privacy of Face by De-Identification Pipeline Based on Deep Learning;2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS);2022-10
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