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

Xia Y, Xu Y, Li S, Wang R, Du J, Cremers D, Stilla U (2021)

Publication Type: Conference contribution

Publication year: 2021

Journal

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society; 1999

Publisher: IEEE Computer Society

Pages Range: 11343-11352

Conference Proceedings Title: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Event location: Virtual, Online, USA

ISBN: 9781665445092

DOI: 10.1109/CVPR46437.2021.01119

Abstract

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 called Hard Positive Hard Negative quadruplet loss (HPHN quadruplet), that achieves better performance than the commonly used metric learning loss. Experiments on various benchmark datasets demonstrate superior performance of the proposed network over the current state-of-the-art approaches. Our code is released publicly at https://github.com/Yan-Xia/SOE-Net.

Involved external institutions

Beijing Institute of Technology (BIT) / 北京理工大学 CN China (CN) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Xia, Y., Xu, Y., Li, S., Wang, R., Du, J., Cremers, D., & Stilla, U. (2021). SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (pp. 11343-11352). Virtual, Online, USA: IEEE Computer Society.

MLA:

Xia, Yan, et al. "SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition." Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2021, Virtual, Online, USA IEEE Computer Society, 2021. 11343-11352.

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