那些让人耳目一新的深度学习图像超分辨率重建方法
本文章只记录（按时间），不分析网络结构、优劣。可能会有遗漏，见谅.
1. SRCNN -- ECCV2014
paper：Learning a Deep Convolutional Network for Image Super-Resolution
source code： http://mmlab.ie.cuhk.edu.hk/projects/SRCNN.html
tensorflow code :https://github.com/tegg89/SRCNN-Tensorflow
2. FSRCNN -- ECCV2016
paper：Accelerating the Super-Resolution Convolutional Neural Network
source code：http://mmlab.ie.cuhk.edu.hk/projects/FSRCNN.html
tensorflow code:https://github.com/yifanw90/FSRCNN-TensorFlow
pyTorch code：https://github.com/yippp/FSRCNN
3. ESPCN -- CVPR2016
paper：Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
tensorflow code：https://github.com/drakelevy/ESPCN-TensorFlow
pyTorch code：https://github.com/leftthomas/ESPCN
4. VDSR -- CVPR2016
paper：Accurate Image Super-Resolution Using Very Deep Convolutional Networks
source code: https://cv.snu.ac.kr/research/VDSR/
tensorflow code：https://github.com/Jongchan/tensorflow-vdsr
pyTorch code：https://github.com/twtygqyy/pytorch-vdsr
5. DRCN -- CVPR2016
paper：Deeply-Recursive Convolutional Network for Image Super-Resolution
source code： https://cv.snu.ac.kr/research/DRCN/
tensorflow code：https://github.com/jiny2001/deeply-recursive-cnn-tf
pyTorch code：https://github.com/fungtion/DRCN
6. RED -- NIPS2016
paper：Image Restoration Using Convolutional Auto-encoders with Symmetric Skip Connections
pyTorch code：https://github.com/yjn870/REDNet-pytorch
https://github.com/JindongJiang/RedNet
7. DRRN -- CVPR2017
paper：Image Super-Resolution via Deep Recursive Residual Network
pyTorch code：https://github.com/jt827859032/DRRN-pytorch
8. LapSRN -- CVPR2017
paper：Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
source code：http://vllab.ucmerced.edu/wlai24/LapSRN/
tensorflow code：https://github.com/zjuela/LapSRN-tensorflow
pyTorch code：https://github.com/twtygqyy/pytorch-LapSRN
9. SRDenseNet -- ICCV2017
paper：Image Super-Resolution Using Dense Skip Connections
tensorflow code：https://github.com/ppooiiuuyh/SR_SRDenseNet_tensorflow
python code：https://github.com/wxywhu/SRDenseNet-pytorch
10. SRGAN(SRResNet) -- CVPR2017（Perceptual Loss）
paper：Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
tensorflow code：https://github.com/tensorlayer/srgan
https://github.com/brade31919/SRGAN-tensorflow
pyTorch code：https://github.com/leftthomas/SRGAN
https://github.com/aitorzip/PyTorch-SRGAN
Perceptual Loss ：
paper：Perceptual Losses for Real-Time Style Transfer and Super-Resolution
project：https://cs.stanford.edu/people/jcjohns/eccv16/
11. EDSR -- CVPRW2017（state-of-the-art）
paper：Enhanced Deep Residual Networks for Single Image Super-Resolution
tensorflow code：https://github.com/jmiller656/EDSR-Tensorflow
pyTorch code：https://github.com/thstkdgus35/EDSR-PyTorch
18年之后的就有点多了，这里挑了几个有意思的列举
12. RDN -- CVPR2018
paper：Residual Dense Network for Image Super-Resolution
tensorflow code：https://github.com/hengchuan/RDN-TensorFlow
pyTorch code：https://github.com/lingtengqiu/RDN-pytorch
13. IDN -- CVPR2018
paper：Fast and Accurate Single Image Super-Resolution via Information Distillation Network
tensorflow code：https://github.com/Zheng222/IDN-tensorflow
pyTorch code：https://github.com/lizhengwei1992/IDN-pytorch
14. DBPN -- CVPR2018
paper：Deep Back-Projection Networks For Super-Resolution
tensorflow code：https://github.com/tlokeshkumar/DBPN-tf
PyTorch code：https://github.com/alterzero/DBPN-Pytorch
15. RCAN -- ECCV2018
paper：Image Super-Resolution Using Very Deep Residual Channel Attention Networks
tensorflow code：https://github.com/kozistr/rcan-tensorflow
pyTorch code：https://github.com/yulunzhang/RCAN
2018CVPR转http://openaccess.thecvf.com/CVPR2018.py
2019 CVPR-SR转：http://bbs.cvmart.net/topics/302/cvpr2019paper#11
reference:
1. https://zhuanlan.zhihu.com/p/31664818
2. https://github.com/YapengTian/Single-Image-Super-Resolution