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

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Showing 401–450 of 1459 papers

TitleStatusHype
Bracketing Image Restoration and Enhancement with High-Low Frequency DecompositionCode2
CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration—0
AdaIR: Exploiting Underlying Similarities of Image Restoration Tasks with Adapters—0
Improving Bracket Image Restoration and Enhancement with Flow-guided Alignment and Enhanced Feature Aggregation—0
Referring Flexible Image RestorationCode1
OmniSSR: Zero-shot Omnidirectional Image Super-Resolution using Stable Diffusion Model—0
Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language ModelsCode4
Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image EnhancementCode1
Joint Conditional Diffusion Model for Image Restoration with Mixed Degradations—0
Rethinking Transformer-Based Blind-Spot Network for Self-Supervised Image DenoisingCode2
Single Stage Adaptive Multi-Attention Network for Image RestorationCode0
Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral ImagesCode0
STAIC regularization for spatio-temporal image reconstruction—0
Empowering Image Recovery_ A Multi-Attention Approach—0
DiffBody: Human Body Restoration by Imagining with Generative Diffusion Prior—0
Dynamic Pre-training: Towards Efficient and Scalable All-in-One Image RestorationCode2
Flare-Free Vision: Empowering Uformer with Depth InsightsCode1
IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions—0
GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration—0
Towards Image Ambient Lighting NormalizationCode1
Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models—0
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational AutoencoderCode0
Self-Rectifying Diffusion Sampling with Perturbed-Attention GuidanceCode3
Distilling Semantic Priors from SAM to Efficient Image Restoration Models—0
Omni-Kernel Network for Image RestorationCode2
Graph Image Prior for Unsupervised Dynamic Cardiac Cine MRI ReconstructionCode1
Latent Neural Cellular Automata for Resource-Efficient Image Restoration—0
Osmosis: RGBD Diffusion Prior for Underwater Image Restoration—0
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and ModulationCode3
Step-Calibrated Diffusion for Biomedical Optical Image RestorationCode0
DeblurDiNAT: A Compact Model with Exceptional Generalization and Visual Fidelity on Unseen DomainsCode1
Multispectral Image Restoration by Generalized Opponent Transformation Total Variation—0
Divide-and-Conquer Posterior Sampling for Denoising Diffusion PriorsCode1
CasSR: Activating Image Power for Real-World Image Super-Resolution—0
VmambaIR: Visual State Space Model for Image RestorationCode3
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion ModelCode2
A Spectrum-based Image Denoising Method with Edge Feature Enhancement—0
How Powerful Potential of Attention on Image Restoration?—0
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint—0
BlindDiff: Empowering Degradation Modelling in Diffusion Models for Blind Image Super-ResolutionCode1
D-YOLO a robust framework for object detection in adverse weather conditions—0
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted DataCode1
Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network StructureCode1
Efficient Diffusion Model for Image Restoration by Residual ShiftingCode5
Boosting Image Restoration via Priors from Pre-trained Models—0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Decoupled Data Consistency with Diffusion Purification for Image RestorationCode1
Segmentation Guided Sparse Transformer for Under-Display Camera Image Restoration—0
Generalizing to Out-of-Sample Degradations via Model ReprogrammingCode0
Decoupling Degradations with Recurrent Network for Video Restoration in Under-Display CameraCode1
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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