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 726–750 of 1459 papers

TitleStatusHype
Toward Interactive Modulation for Photo-Realistic Image Restoration—0
Toward Moiré-Free and Detail-Preserving Demosaicking—0
Towards Context-aware Convolutional Network for Image Restoration—0
Towards Efficient Single Image Dehazing and Desnowing—0
Towards properties of adversarial image perturbations—0
Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration—0
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration—0
Training a Task-Specific Image Reconstruction Loss—0
Training-Free Large Model Priors for Multiple-in-One Image Restoration—0
Training Patch Analysis and Mining Skills for Image Restoration Deep Neural Networks—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
Training Your Image Restoration Network Better with Random Weight Network as Optimization Function—0
CSI-Inpainter: Enabling Visual Scene Recovery from CSI Time Sequences for Occlusion Removal—0
Truncated Nuclear Norm Minimization for Image Restoration Based On Iterative Support Detection—0
TSFormer: A Robust Framework for Efficient UHD Image Restoration—0
Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution—0
U2-Former: A Nested U-shaped Transformer for Image Restoration—0
U2NeRF: Unsupervised Underwater Image Restoration and Neural Radiance Fields—0
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results—0
UG^2: a Video Benchmark for Assessing the Impact of Image Restoration and Enhancement on Automatic Visual Recognition—0
UGPNet: Universal Generative Prior for Image Restoration—0
UHD Image Dehazing via anDehazeFormer with Atmospheric-aware KV Cache—0
Uncertainty Quantification via Neural Posterior Principal Components—0
Understanding Opportunities for Efficiency in Single-image Super Resolution Networks—0
Underwater image filtering: methods, datasets and evaluation—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