Holistically-Nested Edge Detection

@article{Xie2015HolisticallyNestedED,
  title={Holistically-Nested Edge Detection},
  author={Saining Xie and Zhuowen Tu},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={1395-1403}
}
We develop a new edge detection algorithm that addresses two important issues in this long-standing vision problem: (1) holistic image training and prediction; and (2) multi-scale and multi-level feature learning. Our proposed method, holistically-nested edge detection (HED), performs image-to-image prediction by means of a deep learning model that leverages fully convolutional neural networks and deeply-supervised nets. HED automatically learns rich hierarchical representations (guided by deep… CONTINUE READING
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