MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution

@article{Mehri2021MPRNetMR,
  title={MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution},
  author={Armin Mehri and Parichehr Behjati Ardakani and Angel Domingo Sappa},
  journal={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  year={2021},
  pages={2703-2712}
}
Lightweight super resolution networks have extremely importance for real-world applications. In recent years several SR deep learning approaches with outstanding achievement have been introduced by sacrificing memory and computational cost. To overcome this problem, a novel lightweight super resolution network is proposed, which improves the SOTA performance in lightweight SR and performs roughly similar to computationally expensive networks. Multi-Path Residual Network designs with a set of… 

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