Densely connected multidilated convolutional networks for dense prediction tasks

@article{Takahashi2020DenselyCM,
  title={Densely connected multidilated convolutional networks for dense prediction tasks},
  author={Naoya Takahashi and Yuki Mitsufuji},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020},
  pages={993-1002}
}
  • Naoya TakahashiYuki Mitsufuji
  • Published 21 November 2020
  • Computer Science
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Tasks that involve high-resolution dense prediction require a modeling of both local and global patterns in a large input field. Although the local and global structures often depend on each other and their simultaneous modeling is important, many convolutional neural network (CNN)-based approaches interchange representations in different resolutions only a few times. In this paper, we claim the importance of a dense simultaneous modeling of multiresolution representation and propose a novel… 

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