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 501–525 of 1459 papers

TitleStatusHype
NTIRE 2025 challenge on Text to Image Generation Model Quality Assessment—0
UHD Image Dehazing via anDehazeFormer with Atmospheric-aware KV Cache—0
Adaptive Image Restoration for Video Surveillance: A Real-Time Approach—0
Towards a Universal Image Degradation Model via Content-Degradation DisentanglementCode0
LatentINDIGO: An INN-Guided Latent Diffusion Algorithm for Image Restoration—0
Trustworthy Image Super-Resolution via Generative PseudoinverseCode0
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems—0
Behind the Noise: Conformal Quantile Regression Reveals Emergent Representations—0
Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework—0
UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration—0
EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution—0
Multi-Scale Target-Aware Representation Learning for Fundus Image Enhancement—0
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution—0
DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image RestorationCode0
DPMambaIR:All-in-One Image Restoration via Degradation-Aware Prompt State Space Model—0
Distribution-aware Dataset Distillation for Efficient Image Restoration—0
Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration—0
Any Image Restoration via Efficient Spatial-Frequency Degradation Adaptation—0
Circular Image Deturbulence using Quasi-conformal Geometry—0
AdaQual-Diff: Diffusion-Based Image Restoration via Adaptive Quality Prompting—0
Saliency-Aware Diffusion Reconstruction for Effective Invisible Watermark RemovalCode0
HyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration—0
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging—0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Enhancing Image Restoration through Learning Context-Rich and Detail-Accurate FeaturesCode0
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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