Path-Restore: Learning Network Path Selection for Image Restoration

@article{Yu2021PathRestoreLN,
  title={Path-Restore: Learning Network Path Selection for Image Restoration},
  author={K. Yu and Xintao Wang and Chao Dong and Xiaoou Tang and Chen Change Loy},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2021},
  volume={PP}
}
Very deep Convolutional Neural Networks (CNNs) have greatly improved the performance on various image restoration tasks. However, this comes at a price of increasing computational burden, hence limiting their practical usages. We observe that some corrupted image regions are inherently easier to restore than others since the distortion and content vary within an image. To leverage this, we propose Path-Restore, a multi-path CNN with a pathfinder that can dynamically select an appropriate route… 
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