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 51–100 of 1459 papers

TitleStatusHype
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
A Preliminary Study for GPT-4o on Image RestorationCode1
SVAD: From Single Image to 3D Avatar via Synthetic Data Generation with Video Diffusion and Data AugmentationCode2
EAM: Enhancing Anything with Diffusion Transformers for Blind Super-Resolution—0
Image Restoration via Multi-domain LearningCode1
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
Acquire and then Adapt: Squeezing out Text-to-Image Model for Image Restoration—0
Distribution-aware Dataset Distillation for Efficient 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
Deep Generative Models for Bayesian Inference on High-Rate Sensor Data: Applications in Automotive Radar and Medical Imaging—0
HyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration—0
An Efficient and Mixed Heterogeneous Model for Image RestorationCode2
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
Enhancing Image Restoration through Learning Context-Rich and Detail-Accurate FeaturesCode0
Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image RestorationCode1
VibrantLeaves: A principled parametric image generator for training deep restoration modelsCode0
PG-DPIR: An efficient plug-and-play method for high-count Poisson-Gaussian inverse problems—0
Progressive Transfer Learning for Multi-Pass Fundus Image Restoration—0
Computationally iterative methods for salt-and-pepper denoising—0
Beyond Degradation Conditions: All-in-One Image Restoration via HOG TransformersCode1
SIDL: A Real-World Dataset for Restoring Smartphone Images with Dirty Lenses—0
ZipIR: Latent Pyramid Diffusion Transformer for High-Resolution Image Restoration—0
VL-UR: Vision-Language-guided Universal Restoration of Images Degraded by Adverse Weather Conditions—0
Rethinking LayerNorm in Image Restoration TransformersCode2
Q-Agent: Quality-Driven Chain-of-Thought Image Restoration Agent through Robust Multimodal Large Language Model—0
AstroClearNet: Deep image prior for multi-frame astronomical image restoration—0
Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision—0
Content-Aware Transformer for All-in-one Image RestorationCode2
DA2Diff: Exploring Degradation-aware Adaptive Diffusion Priors for All-in-One Weather Restoration—0
Finding the Reflection Point: Unpadding Images to Remove Data Augmentation Artifacts in Large Open Source Image Datasets for Machine Learning—0
Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal—0
Bridge the Gap between SNN and ANN for Image Restoration—0
Deconver: A Deconvolutional Network for Medical Image SegmentationCode0
InstructRestore: Region-Customized Image Restoration with Human InstructionsCode1
indiSplit: Bringing Severity Cognizance to Image Decomposition in Fluorescence Microscopy—0
RELD: Regularization by Latent Diffusion Models for Image Restoration—0
Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration—0
Invert2Restore: Zero-Shot Degradation-Blind Image Restoration—0
Diffusion Image Prior—0
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
Cat-AIR: Content and Task-Aware All-in-One 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