SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition

@article{Xia2021SOENetAS,
  title={SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition},
  author={Yan Xia and Yusheng Xu and Shuang Li and Rui Wang and Juan Du and Daniel Cremers and Uwe Stilla},
  journal={2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021},
  pages={11343-11352}
}
  • Yan Xia, Yusheng Xu, Uwe Stilla
  • Published 24 November 2020
  • Computer Science
  • 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We tackle the problem of place recognition from point cloud data and introduce a self-attention and orientation encoding network (SOE-Net) that fully explores the relationship between points and incorporates long-range context into point-wise local descriptors. Local information of each point from eight orientations is captured in a PointOE module, whereas long-range feature dependencies among local descriptors are captured with a self-attention unit. Moreover, we propose a novel loss function… 
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