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 76100 of 1459 papers

TitleStatusHype
An Intelligent Agentic System for Complex Image Restoration ProblemsCode2
Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality EvaluatorCode2
Efficient Frequency Domain-based Transformers for High-Quality Image DeblurringCode2
An Efficient and Mixed Heterogeneous Model for Image RestorationCode2
Efficient Visual State Space Model for Image DeblurringCode2
BaryIR: Learning Multi-Source Unified Representation in Continuous Barycenter Space for Generalizable All-in-One Image RestorationCode2
Benchmarking Laparoscopic Surgical Image Restoration and BeyondCode2
HIR-Diff: Unsupervised Hyperspectral Image Restoration Via Improved Diffusion ModelsCode2
I^2SB: Image-to-Image Schrödinger BridgeCode2
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture ModelsCode2
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-ResolutionCode2
CascadedGaze: Efficiency in Global Context Extraction for Image RestorationCode2
Learning A Sparse Transformer Network for Effective Image DerainingCode2
Learning Efficient and Effective Trajectories for Differential Equation-based Image RestorationCode2
Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image RestorationCode2
Dual-domain strip attention for image restorationCode2
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided TransformerCode2
Efficient and Explicit Modelling of Image Hierarchies for Image RestorationCode2
Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image RestorationCode2
DiffIR: Efficient Diffusion Model for Image RestorationCode2
MWFormer: Multi-Weather Image Restoration Using Degradation-Aware TransformersCode2
DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration ModelsCode2
Diffusion Models for Image Restoration and Enhancement -- A Comprehensive SurveyCode2
Show:102550
← PrevPage 4 of 59Next →

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