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 1351–1400 of 1459 papers

TitleStatusHype
MetaUE: Model-based Meta-learning for Underwater Image EnhancementCode0
Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion ModelCode0
MemNet: A Persistent Memory Network for Image RestorationCode0
Robust Deep Ensemble Method for Real-world Image DenoisingCode0
Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging ProblemsCode0
Emphasizing Crucial Features for Efficient Image RestorationCode0
Medium Transmission Map Matters for Learning to Restore Real-World Underwater ImagesCode0
Manifold Modeling in Embedded Space: A Perspective for Interpreting Deep Image PriorCode0
Loss Functions for Neural Networks for Image ProcessingCode0
The SIGTYP 2022 Shared Task on the Prediction of Cognate ReflexesCode0
Saliency-Aware Diffusion Reconstruction for Effective Invisible Watermark RemovalCode0
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image RestorationCode0
A Constrained Deformable Convolutional Network for Efficient Single Image Dynamic Scene Blind Deblurring with Spatially-Variant Motion Blur Kernels EstimationCode0
Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy DataCode0
LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CTCode0
Learning Discriminative Shrinkage Deep Networks for Image DeconvolutionCode0
SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategyCode0
Learning Deep CNN Denoiser Prior for Image RestorationCode0
Latent Convolutional ModelsCode0
ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative TransformerCode0
Kernel-aware Burst Blind Super-ResolutionCode0
Sea-ing in Low-lightCode0
Cross-Stitched Multi-task Dual Recursive Networks for Unified Single Image Deraining and DesnowingCode0
Dual Residual Networks Leveraging the Potential of Paired Operations for Image RestorationCode0
Crafting a Toolchain for Image Restoration by Deep Reinforcement LearningCode0
Dual High-Order Total Variation Model for Underwater Image RestorationCode0
Convolutional versus Self-Organized Operational Neural Networks for Real-World Blind Image DenoisingCode0
Segmentation-Aware Image Denoising without Knowing True SegmentationCode0
DriftRec: Adapting diffusion models to blind JPEG restorationCode0
Dual Degradation Representation for Joint Deraining and Low-Light Enhancement in the DarkCode0
Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch NetworkCode0
Iterative Residual CNNs for Burst Photography ApplicationsCode0
An Educated Warm Start For Deep Image Prior-Based Micro CT ReconstructionCode0
Bayesian Image Restoration for Poisson Corrupted Image using a Latent Variational Method with Gaussian MRFCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Self-Guided Network for Fast Image DenoisingCode0
xUnit: Learning a Spatial Activation Function for Efficient Image RestorationCode0
Distilling Image Dehazing With Heterogeneous Task ImitationCode0
Inverse Problems with Diffusion Models: A MAP Estimation PerspectiveCode0
Self-Refining Deep Symmetry Enhanced Network for Rain RemovalCode0
Distilled Pooling Transformer Encoder for Efficient Realistic Image DehazingCode0
Towards a Universal Image Degradation Model via Content-Degradation DisentanglementCode0
Inverse problem regularization with hierarchical variational autoencodersCode0
Intra and Inter Parser-Prompted Transformers for Effective Image RestorationCode0
Improved Techniques for Learning to Dehaze and Beyond: A Collective StudyCode0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater ImagingCode0
Image Super-Resolution as a Defense Against Adversarial AttacksCode0
Image Restoration Using Very Deep Convolutional Encoder-Decoder Networks with Symmetric Skip ConnectionsCode0
DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-ConsistencyCode0
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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