Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation

@article{Yan2016CombiningTB,
  title={Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation},
  author={Zhicheng Yan and Hao Zhang and Yangqing Jia and Thomas Breuel and Yizhou Yu},
  journal={CoRR},
  year={2016},
  volume={abs/1603.04871}
}
State-of-the-art results of semantic segmentation are established by Fully Convolutional neural Networks (FCNs). FCNs rely on cascaded convolutional and pooling layers to gradually enlarge the receptive fields of neurons, resulting in an indirect way of modeling the distant contextual dependence. In this work, we advocate the use of spatially recurrent layers (i.e. ReNet layers) which directly capture global contexts and lead to improved feature representations. We demonstrate the effectiveness… CONTINUE READING
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