Methods › Computer Vision › Face Restoration Models › GFP-GAN
GFP-GAN
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
GFP-GAN is a generative adversarial network for blind face restoration that leverages a generative facial prior (GFP). This Generative Facial Prior (GFP) is incorporated into the face restoration process via channel-split spatial feature transform layers, which allow for a good balance between realness and fidelity. As a whole, the GFP-GAN consists of a degradation removal module (U-Net) and a pretrained face StyleGAN as a facial prior. They are bridged by a latent code mapping and several Channel-Split Spatial Feature Transform (CS-SFT) layers. During training, 1) intermediate restoration losses are employed to remove complex degradation, 2) Facial component loss with discriminators is used to enhance facial details, and 3) identity preserving loss is used to retain face identity.
Papers archive 2025-07-28
3 shown of 3, 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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Arc2Face: A Foundation Model for ID-Consistent Human Faces 18 Mar 2024 · 3 repositories · arXiv:2403.11641Syntology ran 1 of 4 samples · 3 unverified · 3 pointer-only (licence)
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Boosting Cross-Quality Face Verification using Blind Face Restoration 15 Aug 2023 · 0 repositories · arXiv:2308.07967
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Towards Real-World Blind Face Restoration with Generative Facial Prior 11 Jan 2021 · 1 repository · arXiv:2101.04061
Tasks archive 2025-07-28
7 tasks 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 |
|---|---|
| Blind Face Restoration | 2 |
| Face Recognition | 2 |
| Diffusion Personalization | 1 |
| Diffusion Personalization Tuning Free | 1 |
| Face Generation | 1 |
| Face Verification | 1 |
| Video Super-Resolution | 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
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