https://github.com/mingtaoguo/residual-dense-network-trained-with-cgan-for-super-resolution
This repository is as a research project in the field of super resolution. It uses RDN as the generator and spectral norm is used in discriminator.
https://github.com/mingtaoguo/residual-dense-network-trained-with-cgan-for-super-resolution
cgan rdn superresolution tensorflow
Last synced: 3 months ago
JSON representation
This repository is as a research project in the field of super resolution. It uses RDN as the generator and spectral norm is used in discriminator.
- Host: GitHub
- URL: https://github.com/mingtaoguo/residual-dense-network-trained-with-cgan-for-super-resolution
- Owner: MingtaoGuo
- License: mit
- Created: 2018-12-21T12:25:12.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2020-06-05T07:53:33.000Z (over 5 years ago)
- Last Synced: 2025-04-05T13:11:18.337Z (7 months ago)
- Topics: cgan, rdn, superresolution, tensorflow
- Language: Python
- Size: 955 KB
- Stars: 25
- Watchers: 1
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Residual-Dense-Network-Trained-with-cGAN-for-Super-Resolution
This repository is as a research project in the field of super resolution. It uses RDN as the generator and spectral norm is used in discriminator.# Introduction
### This is a trial for super-resolution
The residual dense network has many advantages for reconstructing SR images, and we use GANs to enhance RDN.
The core idea is from the following two papers:
1. Residual Dense Network for Image Super-Resolution
2. cGANs with projection discriminator
##### Generator: Residual Dense Network

##### Discriminator: cGAN projection

# Results
These results is just trained about 200,000 iterations (full: 600,000) with batch size of 16.|Raw|Bicubic(x4)|RDN_GAN(x4)|
|-|-|-|
||||
||||
||||
||||
||||
# Reference
[1] Zhang Y, Tian Y, Kong Y, et al. Residual dense network for image super-resolution[C]//The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2018.[2] Miyato T, Koyama M. cGANs with projection discriminator[J]. arXiv preprint arXiv:1802.05637, 2018.