Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018)
In contrast to other CNN-based SISR methods which only take the LR image as input and lack scalability to handle other degradations, the proposed network takes the concatenated LR image and degradation maps as input, thus allowing a single model to manipulate multiple and even spatially variant degradations.
@inproceedings{zhang2018learning,
title={Learning a Single Convolutional Super-Resolution Network for Multiple Degradations},
author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
year={2018},
}
引用
Kai Zhang (2024). Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (https://github.com/cszn/SRMD), GitHub. 取得済み .
MATLAB リリースの互換性
プラットフォームの互換性
Windows macOS Linuxカテゴリ
- AI, Data Science, and Statistics > Deep Learning Toolbox > Sequence and Numeric Feature Data Workflows >
タグ
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!TrainingCodes
TrainingCodes/kernels
TrainingCodes/utilities
models
utilities
GitHub の既定のブランチを使用するバージョンはダウンロードできません
バージョン | 公開済み | リリース ノート | |
---|---|---|---|
1.0.0.0 | Updata title. Update description. |
|