Face Restoration Models
DFDNet
Introduced by Li et al. in Blind Face Restoration via Deep Multi-scale Component DictionariesDFDNet, 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.
Source: Blind Face Restoration via Deep Multi-scale Component Dictionaries
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
