Enhanced Deep Residual Networks for Single Image Super-Resolution

@article{Lim2017EnhancedDR,
  title={Enhanced Deep Residual Networks for Single Image Super-Resolution},
  author={Bee Lim and Sanghyun Son and Heewon Kim and Seungjun Nah and Kyoung Mu Lee},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2017},
  pages={1132-1140}
}
Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN). In particular, residual learning techniques exhibit improved performance. In this paper, we develop an enhanced deep super-resolution network (EDSR) with performance exceeding those of current state-of-the-art SR methods. The significant performance improvement of our model is due to optimization by removing unnecessary modules in conventional residual networks. The performance… CONTINUE READING
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