Collection of single image super resolution
A list of the methods for single image super-resolution from 2014 to 2018
By Feng Li(if you have any suggestions, please contact me! Email:l1feng @bjtu.edu.cn)
[1] R. Timofte, V. De Smet, and L. Van Gool. A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution. In ACCV, 2014 [Paper] [Code].
[2] Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang. Learning a Deep Convolutional Network for Image Super-Resolution. In ECCV, 2014 [Paper] [Code].
[3] C.-Y. Yang, C. Ma, and M.-H. Yang. Single-image superresolution: A benchmark. In Proceedings of European Conference on Computer Vision (ECCV, 2014). [Paper] [Code].
[4] Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja. Single Image Super-Resolution from Transformed Self-Exemplars. In CVPR, 2015. [Paper] [Code].
[5] S. Schulter, C. Leistner, and H. Bischof. Fast and accurate image upscaling with super-resolution forests. In CVPR, 2015 [Paper] [Code].
[6] Z. Wang, D. Liu, J. Yang, W. Han, and T. Huang. Deep networks for image super-resolution with sparse prior. In ICCV, 2015. [Paper] [Code].
[7] J. SJ. Ren, L. Xu, Q. Yan, and W. Sun. Shepard convolutional neural networks. In NIPS, 2015. [Paper].
[8] S. Gu et al. Convolutional sparse coding for image super-resolution. In ICCV, 2015 [Paper].
[9] K Zeng, J Yu, R Wang, C Li, D Tao. Coupled Deep Autoencoder for Single Image Super-Resolution In IEEE Trans. Cyber., 2015 [Paper] [Code]
[10] Jiwon Kim, Jung Kwon Lee and Kyoung Mu Lee. Accurate Image Super-Resolution Using Very Deep Convolutional Networks. In CVPR, 2016. [Paper] [Code].