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 476–500 of 1459 papers

TitleStatusHype
Unified-Width Adaptive Dynamic Network for All-In-One Image RestorationCode1
LLMRA: Multi-modal Large Language Model based Restoration Assistant—0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
Deep Linear Array Pushbroom Image Restoration: A Degradation Pipeline and Jitter-Aware Restoration NetworkCode1
LiDAR Depth Map Guided Image Compression Model—0
Content-Aware Depth-Adaptive Image Restoration—0
Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning StrategyCode2
MirrorDiffusion: Stabilizing Diffusion Process in Zero-shot Image Translation by Prompts Redescription and Beyond—0
Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier DomainCode1
Image Restoration: A Comparative Analysis of Image De noising Using Different Spatial Filtering Techniques—0
Multimodal Prompt Perceiver: Empower Adaptiveness Generalizability and Fidelity for All-in-One Image Restoration—0
Look-Up Table Compression for Efficient Image RestorationCode1
CoDe: An Explicit Content Decoupling Framework for Image Restoration—0
Generative Latent Coding for Ultra-Low Bitrate Image Compression—0
Learning Diffusion Texture Priors for Image Restoration—0
Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image RestorationCode2
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
UGPNet: Universal Generative Prior for Image Restoration—0
Improving Image Restoration through Removing Degradations in Textual RepresentationsCode1
Restoration by Generation with Constrained Priors—0
Personalized Restoration via Dual-Pivot Tuning—0
DarkShot: Lighting Dark Images with Low-Compute and High-Quality—0
Efficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation—0
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned GuidanceCode1
MuLA-GAN: Multi-Level Attention GAN for Enhanced Underwater Visibility—0
Show:102550
← PrevPage 20 of 59Next →
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