Unsupervised Learning of Edges

@article{Li2016UnsupervisedLO,
  title={Unsupervised Learning of Edges},
  author={Y. Li and Manohar Paluri and James M. Rehg and Piotr Doll{\'a}r},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={1619-1627}
}
  • Y. Li, Manohar Paluri, +1 author Piotr Dollár
  • Published 2016
  • Computer Science
  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • Data-driven approaches for edge detection have proven effective and achieve top results on modern benchmarks. However, all current data-driven edge detectors require manual supervision for training in the form of hand-labeled region segments or object boundaries. Specifically, human annotators mark semantically meaningful edges which are subsequently used for training. Is this form of strong, highlevel supervision actually necessary to learn to accurately detect edges? In this work we present a… CONTINUE READING
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