Super-resolution of very low-resolution face images with a wavelet integrated, identity preserving, adversarial network
Author:
Publisher
Elsevier BV
Subject
Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software
Reference43 articles.
1. Face hallucination: Theory and practice;Liu;Int. J. Comput. Vis.,2007
2. Image super-resolution using deep convolutional networks;Dong;IEEE Trans. Pattern Anal. Mach. Intell.,2016
3. J. Kim, J.K. Lee, K.M. Lee, Accurate Image Super-Resolution Using Very Deep Convolutional Networks, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 1646–1654.
4. J. Kim, J.K. Lee, K.M. Lee, Deeply-Recursive Convolutional Network for Image Super-Resolution, in: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 1637–1645.
5. C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, W. Shi, Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 105–114.
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