Methods › Computer Vision › Generative Adversarial Networks › PrivacyNet
PrivacyNet
Introduced by Vahid Mirjalili et al. in PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
PrivacyNet is a GAN-based semi-adversarial network (SAN) that modifies an input face image such that it can be used by a face matcher for matching purposes but cannot be reliably used by an attribute classifier. PrivacyNet allows a person to choose specific attributes that have to be obfuscated in the input face images (e.g., age and race), while allowing for other types of attributes to be extracted (e.g., gender).
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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PrivacyNet: Semi-Adversarial Networks for Multi-attribute Face Privacy 2 Jan 2020 · 0 repositories · arXiv:2001.00561
Tasks archive 2025-07-28
1 task the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
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| Attribute | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections