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 751–800 of 1459 papers

TitleStatusHype
Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral ImagesCode0
STAIC regularization for spatio-temporal image reconstruction—0
Empowering Image Recovery_ A Multi-Attention Approach—0
DiffBody: Human Body Restoration by Imagining with Generative Diffusion Prior—0
GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration—0
IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions—0
Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models—0
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational AutoencoderCode0
Distilling Semantic Priors from SAM to Efficient Image Restoration Models—0
Latent Neural Cellular Automata for Resource-Efficient Image Restoration—0
Osmosis: RGBD Diffusion Prior for Underwater Image Restoration—0
Step-Calibrated Diffusion for Biomedical Optical Image RestorationCode0
Multispectral Image Restoration by Generalized Opponent Transformation Total Variation—0
CasSR: Activating Image Power for Real-World Image Super-Resolution—0
A Spectrum-based Image Denoising Method with Edge Feature Enhancement—0
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint—0
How Powerful Potential of Attention on Image Restoration?—0
D-YOLO a robust framework for object detection in adverse weather conditions—0
Boosting Image Restoration via Priors from Pre-trained Models—0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Segmentation Guided Sparse Transformer for Under-Display Camera Image Restoration—0
Generalizing to Out-of-Sample Degradations via Model ReprogrammingCode0
IRConStyle: Image Restoration Framework Using Contrastive Learning and Style TransferCode0
Learning to See Through Dazzle—0
Adversarial Purification and Fine-tuning for Robust UDC Image Restoration—0
Hybrid Training of Denoising Networks to Improve the Texture Acutance of Digital Cameras—0
DestripeCycleGAN: Stripe Simulation CycleGAN for Unsupervised Infrared Image DestripingCode0
Gyroscope-Assisted Motion Deblurring NetworkCode0
Descanning: From Scanned to the Original Images with a Color Correction Diffusion Model—0
Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstruction—0
Knowledge-driven deep learning for fast MR imaging: undersampled MR image reconstruction from supervised to un-supervised learning—0
Rethinking RGB Color Representation for Image Restoration Models—0
Key-Graph Transformer for Image Restoration—0
Diffusion Model Compression for Image-to-Image Translation—0
Spatial-and-Frequency-aware Restoration method for Images based on Diffusion Models—0
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild—0
LLMRA: Multi-modal Large Language Model based Restoration Assistant—0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
LiDAR Depth Map Guided Image Compression Model—0
Content-Aware Depth-Adaptive Image Restoration—0
MirrorDiffusion: Stabilizing Diffusion Process in Zero-shot Image Translation by Prompts Redescription and Beyond—0
Image Restoration: A Comparative Analysis of Image De noising Using Different Spatial Filtering Techniques—0
CoDe: An Explicit Content Decoupling Framework for Image Restoration—0
Learning Diffusion Texture Priors for Image Restoration—0
Multimodal Prompt Perceiver: Empower Adaptiveness Generalizability and Fidelity for All-in-One Image Restoration—0
Generative Latent Coding for Ultra-Low Bitrate Image Compression—0
UGPNet: Universal Generative Prior for Image Restoration—0
DarkShot: Lighting Dark Images with Low-Compute and High-Quality—0
Personalized Restoration via Dual-Pivot Tuning—0
Restoration by Generation with Constrained Priors—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