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 526–550 of 1459 papers

TitleStatusHype
Efficient Progressive High Dynamic Range Image Restoration via Attention and Alignment Network—0
Complexity Experts are Task-Discriminative Learners for Any Image Restoration—0
Holistic Dynamic Frequency Transformer for Image Fusion and Exposure Correction—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Efficient Image Restoration via Latent Consistency Flow Matching—0
A Study on the Efficient Product Search Service for the Damaged Image Information—0
Efficient Image Restoration through Low-Rank Adaptation and Stable Diffusion XL—0
Color graph based wavelet transform with perceptual information—0
AstroClearNet: Deep image prior for multi-frame astronomical image restoration—0
Efficient Dynamic Scene Deblurring Using Spatially Variant Deconvolution Network With Optical Flow Guided Training—0
Efficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation—0
Efficient Degradation-aware Any Image Restoration—0
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
Adaptive Dropout: Unleashing Dropout across Layers for Generalizable Image Super-Resolution—0
Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems—0
Effective Backscatter Approximation for Photometry in Murky Water—0
Coercive functions from a topological viewpoint and properties of minimizing sets of convex functions appearing in image restoration—0
Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression—0
Edge Adaptive Hybrid Regularization Model For Image Deblurring—0
CoDe: An Explicit Content Decoupling Framework for Image Restoration—0
EchoIR: Advancing Image Restoration with Echo Upsampling and Bi-Level Optimization—0
A Spectrum-based Image Denoising Method with Edge Feature Enhancement—0
All-in-One Image Restoration for Unknown Degradations Using Adaptive Discriminative Filters for Specific Degradations—0
H-OWAN: Multi-distorted Image Restoration with Tensor 1x1 Convolution—0
HyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration—0
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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