Methods › Computer Vision › Face Restoration Models › DFDNet
DFDNet
Introduced by Xiaoming Li et al. in Blind Face Restoration via Deep Multi-scale Component Dictionaries
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
DFDNet, or DFDNet, is a deep face dictionary network for face restoration to guide the restoration process of degraded observations. Given a LQ image I_d, the DFDNet selects the dictionary features that have the most similar structure with the input. Specially, we re-norm the whole dictionaries via component AdaIN (termed as CAdaIN) based on the input component to eliminate the distribution or style diversity. The selected dictionary features are then utilized to guide the restoration process via dictionary feature transformation.
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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Blind Face Restoration via Deep Multi-scale Component Dictionaries 2 Aug 2020 · 1 repository · arXiv:2008.00418Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
Tasks archive 2025-07-28
2 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 | 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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