• Corpus ID: 85542864

FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation

@article{Wu2019FastFCNRD,
  title={FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation},
  author={Huikai Wu and Junge Zhang and Kaiqi Huang and Kongming Liang and Yizhou Yu},
  journal={ArXiv},
  year={2019},
  volume={abs/1903.11816}
}
Modern approaches for semantic segmentation usually employ dilated convolutions in the backbone to extract high-resolution feature maps, which brings heavy computation complexity and memory footprint. [] Key Method With the proposed JPU, our method reduces the computation complexity by more than three times without performance loss. Experiments show that JPU is superior to other upsampling modules, which can be plugged into many existing approaches to reduce computation complexity and improve performance. By…
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