Image super‐resolution using conditional generative adversarial network

Author:

Qiao Jiaojiao1,Song Huihui1,Zhang Kaihua1ORCID,Zhang Xiaolu1,Liu Qingshan1

Affiliation:

1. Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and TechnologyNanjing10300People's Republic of China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference25 articles.

1. 2007 IEEE Conf. on Computer Vision and Pattern Recognition. IEEE Computer Society Minneapolis MN USA Q. Yang R. Yang J. Davis Spatial‐depth super resolution for range images 1 8

2. Accurate Image Super-Resolution Using Very Deep Convolutional Networks

3. 2014 European Conf. on Computer Vision Zürich Zürich C. Yang C. Ma M. Yang Single‐image super‐resolution: a benchmark 372 386

4. Learning a Deep Convolutional Network for Image Super-Resolution

5. Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

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