PSFR-GAN is a semantic-aware style transformation framework for face restoration. Given a pair of LQ face image and its corresponding parsing map, we first generate a multi-scale pyramid of the inputs, and then progressively modulate different scale features from coarse-to-fine in a semantic-aware style transfer way. Compared with previous networks, the proposed PSFR-GAN makes full use of the semantic (parsing maps) and pixel (LQ images) space information from different scales of inputs.
Source: Progressive Semantic-Aware Style Transformation for Blind Face RestorationPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Blind Face Restoration | 1 | 25.00% |
Face Parsing | 1 | 25.00% |
Semantic Parsing | 1 | 25.00% |
Style Transfer | 1 | 25.00% |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |