Semantic Binary Segmentation Using Convolutional Networks without Decoders

@article{Aich2018SemanticBS,
  title={Semantic Binary Segmentation Using Convolutional Networks without Decoders},
  author={Shubhra Aich and William van der Kamp and Ian Stavness},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2018},
  pages={182-1824}
}
In this paper, we propose an efficient architecture for semantic image segmentation using the depth-to-space (D2S) operation. Our D2S model is comprised of a standard CNN encoder followed by a depth-to-space reordering of the final convolutional feature maps. Our approach eliminates the decoder portion of traditional encoder-decoder segmentation models and reduces the amount of computation almost by half. As a participant of the DeepGlobe Road Extraction competition, we evaluate our models on… 

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