SOTAVerified

Image Restoration

Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).

Source: Blind Image Restoration without Prior Knowledge

Papers

Showing 501510 of 1459 papers

TitleStatusHype
Breaking Complexity Barriers: High-Resolution Image Restoration with Rank Enhanced Linear Attention0
UHD Image Dehazing via anDehazeFormer with Atmospheric-aware KV Cache0
LatentINDIGO: An INN-Guided Latent Diffusion Algorithm for Image Restoration0
Adaptive Image Restoration for Video Surveillance: A Real-Time Approach0
Towards a Universal Image Degradation Model via Content-Degradation DisentanglementCode0
Trustworthy Image Super-Resolution via Generative PseudoinverseCode0
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems0
Behind the Noise: Conformal Quantile Regression Reveals Emergent Representations0
Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework0
UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72Unverified
2SRUDCAverage PSNR (dB)27.64Unverified
3RestormerAverage PSNR (dB)26.99Unverified
4WGWSNetAverage PSNR (dB)26.96Unverified
5DGUNetAverage PSNR (dB)26.92Unverified
6OKNetAverage PSNR (dB)26.33Unverified
7MIRNetAverage PSNR (dB)25.97Unverified
8PromptIRAverage PSNR (dB)25.9Unverified
9MPRNetAverage PSNR (dB)25.47Unverified
10MIRNetv2Average PSNR (dB)25.37Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42Unverified
2ESDNetPSNR22.12Unverified
#ModelMetricClaimedVerifiedStatus
1730L37Unverified