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 1376–1400 of 1459 papers

TitleStatusHype
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