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 601–625 of 1459 papers

TitleStatusHype
Image Restoration with Locally Selected Class-Adapted Models—0
Disparity-Aware Domain Adaptation in Stereo Image Restoration—0
Discriminative Transfer Learning for General Image Restoration—0
Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restoration—0
A HVS-inspired Attention to Improve Loss Metrics for CNN-based Perception-Oriented Super-Resolution—0
DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration—0
DILIE: Deep Internal Learning for Image Enhancement—0
Dilated Strip Attention Network for Image Restoration—0
Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks—0
Accelerating Large Kernel Convolutions with Nested Winograd Transformation.pdf—0
AccelIR: Task-Aware Image Compression for Accelerating Neural Restoration—0
Image Restoration with Point Spread Function Regularization and Active Learning—0
Building Bridge Across the Time: Disruption and Restoration of Murals In the Wild—0
Are Conditional Latent Diffusion Models Effective for Image Restoration?—0
A higher-order MRF based variational model for multiplicative noise reduction—0
Diffusion Model-based FOD Restoration from High Distortion in dMRI—0
Diffusion Methods for Classification with Pairwise Relationships—0
Diffusion Image Prior—0
Bridging the Gap Between Computational Photography and Visual Recognition—0
Aquatic-GS: A Hybrid 3D Representation for Underwater Scenes—0
AdaIR: Exploiting Underlying Similarities of Image Restoration Tasks with Adapters—0
Bridge the Gap between SNN and ANN for Image Restoration—0
Diff-Unfolding: A Model-Based Score Learning Framework for Inverse Problems—0
Why Are Deep Representations Good Perceptual Quality Features?—0
DiffStereo: High-Frequency Aware Diffusion Model for Stereo 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