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
Adapting Text-to-Image Generation with Feature Difference Instruction for Generic Image Restoration—0
Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering—0
Secret Lies in Color: Enhancing AI-Generated Images Detection with Color Distribution Analysis—0
UniRestorer: Universal Image Restoration via Adaptively Estimating Image Degradation at Proper GranularityCode0
An Ordinary Differential Equation Sampler with Stochastic Start for Diffusion Bridge Models—0
Generative Adversarial Network on Motion-Blur Image Restoration—0
UNet--: Memory-Efficient and Feature-Enhanced Network Architecture based on U-Net with Reduced Skip-Connections—0
NeuroPump: Simultaneous Geometric and Color Rectification for Underwater Images—0
Personalized Generative Low-light Image Denoising and Enhancement—0
Distilled Pooling Transformer Encoder for Efficient Realistic Image DehazingCode0
Consistent Diffusion: Denoising Diffusion Model with Data-Consistent Training for Image Restoration—0
Towards Context-aware Convolutional Network for Image Restoration—0
Boosting ViT-based MRI Reconstruction from the Perspectives of Frequency Modulation, Spatial Purification, and Scale Diversification—0
Matrix Completion via Residual Spectral Matching—0
Are Conditional Latent Diffusion Models Effective for Image Restoration?—0
ExpRDiff: Short-exposure Guided Diffusion Model for Realistic Local Motion Deblurring—0
Convergence Analysis of a Proximal Stochastic Denoising Regularization Algorithm—0
EchoIR: Advancing Image Restoration with Echo Upsampling and Bi-Level Optimization—0
A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing—0
InstantRestore: Single-Step Personalized Face Restoration with Shared-Image Attention—0
Enhancing Sample Generation of Diffusion Models using Noise Level Correction—0
Equivariant Denoisers for Image Restoration—0
ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration—0
Exploring Real&Synthetic Dataset and Linear Attention in Image Restoration—0
Aberration Correcting Vision Transformers for High-Fidelity Metalens Imaging—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