文章目录

• A survey of deep learning approaches to image restoration
• Denoising Prior Driven Deep Neural Network for Image Restoration
• Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging
• Image-to-Image MLP-mixer for Image Reconstruction
• SwinIR: Image Restoration Using Swin Transformer
• Uformer: A General U-Shaped Transformer for Image Restoration
• Restormer: Efficient Transformer for High-Resolution Image Restoration
• Pyramid Attention Networks for Image Restoration
• Residual Non-local Attention Networks for Image Restoration
• Learning Enriched Features for Real Image Restoration and Enhancement
• Multi-Stage Progressive Image Restoration
• CycleISP: Real Image Restoration via Improved Data Synthesis
• Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration
• Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search
• Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning
• Multi-Level Wavelet-CNN for Image Restoration
• Non-Local Recurrent Network for Image Restoration
• Noise2Noise: Learning Image Restoration without Clean Data
• COLA-Net: Collaborative Attention Network for Image Restoration
• EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration
• HINet: Half Instance Normalization Network for Image Restoration
• Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image Restoration
• Residual Dense Network for Image Restoration
• Plug-and-Play Image Restoration with Deep Denoiser Prior
• Path-Restore: Learning Network Path Selection for Image Restoration
• HSI-DeNet: Hyperspectral Image Restoration via Convolutional Neural Network
• Image Restoration Using Total Variation Regularized Deep Image Prior
• Hyperspectral Image Restoration by Tensor Fibered Rank Constrained Optimization and Plug-and-Play Regularization
• Image Restoration by Iterative Denoising and Backward Projections
• Multi-scale adversarial network for underwater image restoration
• Deep learning–based image restoration algorithm for coronary CT angiography

A survey of deep learning approaches to image restoration

Denoising Prior Driven Deep Neural Network for Image Restoration

Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging

Image-to-Image MLP-mixer for Image Reconstruction

SwinIR: Image Restoration Using Swin Transformer

Uformer: A General U-Shaped Transformer for Image Restoration

Restormer: Efficient Transformer for High-Resolution Image Restoration

Pyramid Attention Networks for Image Restoration

Residual Non-local Attention Networks for Image Restoration

Learning Enriched Features for Real Image Restoration and Enhancement

Multi-Stage Progressive Image Restoration

CycleISP: Real Image Restoration via Improved Data Synthesis

Dual Residual Networks Leveraging the Potential of Paired Operations for Image Restoration

Exploiting the Potential of Standard Convolutional Autoencoders for Image Restoration by Evolutionary Search

Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning

Multi-Level Wavelet-CNN for Image Restoration

Non-Local Recurrent Network for Image Restoration

Noise2Noise: Learning Image Restoration without Clean Data

COLA-Net: Collaborative Attention Network for Image Restoration

EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration

HINet: Half Instance Normalization Network for Image Restoration

Interactive Multi-Dimension Modulation with Dynamic Controllable Residual Learning for Image Restoration

Residual Dense Network for Image Restoration

Plug-and-Play Image Restoration with Deep Denoiser Prior

Path-Restore: Learning Network Path Selection for Image Restoration

HSI-DeNet: Hyperspectral Image Restoration via Convolutional Neural Network

Image Restoration Using Total Variation Regularized Deep Image Prior

Hyperspectral Image Restoration by Tensor Fibered Rank Constrained Optimization and Plug-and-Play Regularization

Image Restoration by Iterative Denoising and Backward Projections

Multi-scale adversarial network for underwater image restoration

Deep learning–based image restoration algorithm for coronary CT angiography