learn SISR paper
| 时间 | 论文 | 网络 | 代码 | see | idea |
|---|---|---|---|---|---|
| 2014 | Image Super-Resolution Using Deep Convolutional Networks | SRCNN | https://github.com/yjn870/SRCNN-pytorch | √ | |
| 2016 | Accelerating the Super-Resolution Convolutional Neural Network | FSRCNN | https://github.com/yjn870/FSRCNN-pytorch | √ | |
| 2016 | Deeply-Recursive Convolutional Network for Image Super-Resolution | DRCN | https://github.com/fungtion/DRCN | √ | |
| 2016 | Accurate Image Super-Resolution Using Very Deep Convolutional Networks | VDSR | https://github.com/twtygqyy/pytorch-vdsr | √ | |
| 2018 | Residual Dense Network for Image Super-Resolution | RDCN | https://github.com/yjn870/RDN-pytorch | √ | 将每一层的特征分级的输入到后面的网络中 |
| 2018 | Residual Dense Network for Image Super-Resolution | RDN | https://github.com/yjn870/RDN-pytorch | √ | |
| 2018 | Wide Activation for Efficient and Accurate Image | WDSR | GitHub - 嘉会宇/wdsr_ntire2018：我们赢得NTIRE超分辨率挑战赛的代码，CVPR 2018 | √ | 在进入到激活函数之前可以将特征图变深 |
| 2021 | Coarse-to-Fine CNN for Image Super-Resolution | CFSRCNN | https://github.com/hellloxiaotian/CFSRCNN | √ |