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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–475 of 1459 papers

TitleStatusHype
FriendNet: Detection-Friendly Dehazing NetworkCode1
Dual-domain strip attention for image restorationCode2
Diffusion Posterior Proximal Sampling for Image RestorationCode1
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Learning to See Through Dazzle—0
HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion ModelsCode2
MambaIR: A Simple Baseline for Image Restoration with State-Space ModelCode5
Adversarial Purification and Fine-tuning for Robust UDC Image Restoration—0
Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras—0
DestripeCycleGAN: Stripe Simulation CycleGAN for Unsupervised Infrared Image DestripingCode0
Gyroscope-Assisted Motion Deblurring NetworkCode0
Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model—0
Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction—0
U-shaped Vision Mamba for Single Image DehazingCode2
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning—0
Rethinking RGB Color Representation for Image Restoration Models—0
Key-Graph Transformer for Image Restoration—0
LIR: A Lightweight Baseline for Image RestorationCode1
Plug-and-Play image restoration with Stochastic deNOising REgularizationCode1
Spatial-and-Frequency-aware Restoration method for Images based on Diffusion Models—0
Diffusion Model Compression for Image-to-Image Translation—0
InstructIR: High-Quality Image Restoration Following Human InstructionsCode4
UP-CrackNet: Unsupervised Pixel-Wise Road Crack Detection via Adversarial Image RestorationCode1
CascadedGaze: Efficiency in Global Context Extraction for Image RestorationCode2
Unified-Width Adaptive Dynamic Network for All-In-One Image RestorationCode1
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All datasetsCDD-11UHDM.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72—Unverified
2SRUDCAverage PSNR (dB)27.64—Unverified
3RestormerAverage PSNR (dB)26.99—Unverified
4WGWSNetAverage PSNR (dB)26.96—Unverified
5DGUNetAverage PSNR (dB)26.92—Unverified
6OKNetAverage PSNR (dB)26.33—Unverified
7MIRNetAverage PSNR (dB)25.97—Unverified
8PromptIRAverage PSNR (dB)25.9—Unverified
9MPRNetAverage PSNR (dB)25.47—Unverified
10MIRNetv2Average PSNR (dB)25.37—Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42—Unverified
2ESDNetPSNR22.12—Unverified
#ModelMetricClaimedVerifiedStatus
1730L37—Unverified