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Towards Real-World Blind Face Restoration With Generative Facial Prior

CVPR 2021 · Image generation › Image restoration · approach: Priors for restoration networks · 525 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add multi-resolution spatial modulation to latent code mapping (ablation)GFP-GAN · CelebA-Test blind face restorationLPIPS: 0.550 ($\uparrow$) -> 0.3646Helped
Use CS-SFT instead of standard SFT (ablation)GFP-GAN · CelebA-Test blind face restorationLPIPS: 0.387 ($\uparrow$) -> 0.3646Helped
Add pretrained generative facial prior (ablation)GFP-GAN · CelebA-Test blind face restorationLPIPS: 0.379 ($\uparrow$) -> 0.3646Helped
Add pyramid restoration loss (ablation)GFP-GAN · CelebA-Test blind face restorationLPIPS: 0.369 ($\uparrow$) -> 0.3646Helped
Use CS-SFT instead of standard SFT (ablation)GFP-GAN · CelebA-Test blind face restorationFID: 47.65 ($\uparrow$) -> 42.62Helped
Replace full CS-SFT modulation with standard SFT (ablation)GFP-GAN · CelebA-Test blind face restorationidentity distance (Deg.): 34.60 -> 34.38 ($\downarrow$)Mixed
Add facial component discriminators and feature style loss (ablation)GFP-GAN · CelebA-Test blind face restorationfacial detail qualityHelped
Use Gram-statistics feature style loss rather than feature matching loss (ablation)GFP-GAN facial component loss · CelebA-Test blind face restorationfacial detail qualityHelped

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