Fully Convolutional Instance-Aware Semantic Segmentation

@article{Li2016FullyCI,
  title={Fully Convolutional Instance-Aware Semantic Segmentation},
  author={Yi Li and Haozhi Qi and Jifeng Dai and Xiangyang Ji and Yichen Wei},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={4438-4446}
}
  • Yi LiHaozhi Qi Yichen Wei
  • Published 23 November 2016
  • Computer Science
  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
We present the first fully convolutional end-to-end solution for instance-aware semantic segmentation task. It inherits all the merits of FCNs for semantic segmentation [29] and instance mask proposal [5]. It performs instance mask prediction and classification jointly. The underlying convolutional representation is fully shared between the two sub-tasks, as well as between all regions of interest. The network architecture is highly integrated and efficient. It achieves state-of-the-art… 

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