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

Showing 576600 of 1459 papers

TitleStatusHype
Moire Image Restoration using Multi Level Hyper Vision NetCode0
Multi-level Wavelet Convolutional Neural NetworksCode0
Non-Local Recurrent Network for Image RestorationCode0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
Bengali License Plate Recognition: Unveiling Clarity with CNN and GFP-GANCode0
Microscopy Image Restoration with Deep Wiener-Kolmogorov filtersCode0
Benchmarking Ultra-High-Definition Image Reflection RemovalCode0
MetaUE: Model-based Meta-learning for Underwater Image EnhancementCode0
Deconver: A Deconvolutional Network for Medical Image SegmentationCode0
Bayesian Image Restoration for Poisson Corrupted Image using a Latent Variational Method with Gaussian MRFCode0
A Constrained Deformable Convolutional Network for Efficient Single Image Dynamic Scene Blind Deblurring with Spatially-Variant Motion Blur Kernels EstimationCode0
MemNet: A Persistent Memory Network for Image RestorationCode0
Modular Degradation Simulation and Restoration for Under-Display CameraCode0
Gyroscope-Assisted Motion Deblurring NetworkCode0
Manifold Modeling in Embedded Space: A Perspective for Interpreting Deep Image PriorCode0
Group-based Sparse Representation for Image RestorationCode0
DDR: Exploiting Deep Degradation Response as Flexible Image DescriptorCode0
Medium Transmission Map Matters for Learning to Restore Real-World Underwater ImagesCode0
Loss Functions for Neural Networks for Image ProcessingCode0
Gradient-Guided Parameter Mask for Multi-Scenario Image Restoration Under Adverse WeatherCode0
LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CTCode0
Global-Local Stepwise Generative Network for Ultra High-Resolution Image RestorationCode0
Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image RestorationCode0
Learning Discriminative Shrinkage Deep Networks for Image DeconvolutionCode0
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification LayersCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1OneRestoreAverage PSNR (dB)28.72Unverified
2SRUDCAverage PSNR (dB)27.64Unverified
3RestormerAverage PSNR (dB)26.99Unverified
4WGWSNetAverage PSNR (dB)26.96Unverified
5DGUNetAverage PSNR (dB)26.92Unverified
6OKNetAverage PSNR (dB)26.33Unverified
7MIRNetAverage PSNR (dB)25.97Unverified
8PromptIRAverage PSNR (dB)25.9Unverified
9MPRNetAverage PSNR (dB)25.47Unverified
10MIRNetv2Average PSNR (dB)25.37Unverified
#ModelMetricClaimedVerifiedStatus
1ESDNet-LPSNR22.42Unverified
2ESDNetPSNR22.12Unverified
#ModelMetricClaimedVerifiedStatus
1730L37Unverified