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 1276–1300 of 1459 papers

TitleStatusHype
Mixed Degradation Image Restoration via Local Dynamic Optimization and Conditional Embedding—0
Mobile Image Restoration via Prior Quantization—0
Mockingbird at the SIGTYP 2022 Shared Task: Two Types of Models forthe Prediction of Cognate Reflexes—0
Point Spread Function Estimation for Wide Field Small Aperture Telescopes with Deep Neural Networks and Calibration Data—0
MoE-DiffIR: Task-customized Diffusion Priors for Universal Compressed Image Restoration—0
MoiréXNet: Adaptive Multi-Scale Demoiréing with Linear Attention Test-Time Training and Truncated Flow Matching Prior—0
Motion Deblurring using Spatiotemporal Phase Aperture Coding—0
MRIR: Integrating Multimodal Insights for Diffusion-based Realistic Image Restoration—0
MRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers—0
MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing—0
MuLA-GAN: Multi-Level Attention GAN for Enhanced Underwater Visibility—0
Multi-Agent Image Restoration—0
Multi-bin Trainable Linear Unit for Fast Image Restoration Networks—0
MultiColor: Image Colorization by Learning from Multiple Color Spaces—0
Multi-defect microscopy image restoration under limited data conditions—0
Multiframe-based Adaptive Despeckling Algorithm for Ultrasound B-mode Imaging with Superior Edge and Texture—0
Multi-level Attention-guided Graph Neural Network for Image Restoration—0
Multi-level Encoder-Decoder Architectures for Image Restoration—0
Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal—0
Multimodal Prompt Perceiver: Empower Adaptiveness, Generalizability and Fidelity for All-in-One Image Restoration—0
Multimodal Prompt Perceiver: Empower Adaptiveness Generalizability and Fidelity for All-in-One Image Restoration—0
Multi-Objective CNN Based Algorithm for SAR Despeckling—0
Multi-scale Conditional Generative Modeling for Microscopic Image Restoration—0
Multi-Scale Face Restoration with Sequential Gating Ensemble Network—0
Multi-scale Frequency Enhancement Network for Blind Image Deblurring—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