RANet: Ranking Attention Network for Fast Video Object Segmentation

@article{Wang2019RANetRA,
  title={RANet: Ranking Attention Network for Fast Video Object Segmentation},
  author={Z. Wang and Jun Xu and Li Liu and F. Zhu and Ling Shao},
  journal={2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2019},
  pages={3977-3986}
}
  • Z. Wang, Jun Xu, +2 authors Ling Shao
  • Published 2019
  • Computer Science
  • 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Despite online learning (OL) techniques have boosted the performance of semi-supervised video object segmentation (VOS) methods, the huge time costs of OL greatly restrict their practicality. [...] Key Method Specifically, to integrate the insights of matching based and propagation based methods, we employ an encoder-decoder framework to learn pixel-level similarity and segmentation in an end-to-end manner.Expand Abstract
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