SOTAVerified

Blind Face Restoration

Blind face restoration aims at recovering high-quality faces from the low-quality counterparts suffering from unknown degradation, such as low-resolution, noise, blur, compression artifacts, etc. When applied to real-world scenarios, it becomes more challenging, due to more complicated degradation, diverse poses and expressions.

Description source: Towards Real-World Blind Face Restoration with Generative Facial Prior

Image source: Towards Real-World Blind Face Restoration with Generative Facial Prior

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 55 papers

TitleStatusHype
LAFR: Efficient Diffusion-based Blind Face Restoration via Latent Codebook Alignment Adapter—0
TD-BFR: Truncated Diffusion Model for Efficient Blind Face Restoration—0
IQPFR: An Image Quality Prior for Blind Face Restoration and Beyond—0
InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration—0
InfoBFR: Real-World Blind Face Restoration via Information Bottleneck—0
Binary Diffusion Probabilistic Model—0
FaceMe: Robust Blind Face Restoration with Personal Identification—0
Dynamic Content Prediction with Motion-aware Priors for Blind Face Video Restoration—0
Visual Style Prompt Learning Using Diffusion Models for Blind Face RestorationCode1
RestorerID: Towards Tuning-Free Face Restoration with ID PreservationCode1
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All datasetsCelebA-TestLFWWIDERCelebA-HQ

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Super-FANFID136.83—Unverified
2GWAInetFID135.84—Unverified
3GFRNetFID134.92—Unverified
4Pix2PixHDFID76.89—Unverified
5HiFaceGANFID56.67—Unverified
6GPENFID31.72—Unverified