HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration-Reference-Cited by-同舟云学术

HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Lu Fan¹,Chen Guang¹,Liu Yinlong²,Zhang Lijun¹,Qu Sanqing¹,Liu Shu³,Gu Rongqi⁴

Affiliation:

1. Tongji University

2. Technische Universität München

3. ETH Zurich

4. Westwell lab

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710151.pdf?arnumber=9710151

Reference42 articles.

1. Deepgmr: Learning latent gaussian mixture models for registration;yuan;European Conference on Computer Vision,2020

2. 3dfeat-net: Weakly supervised local 3d features for point cloud registration;yew;Proceedings of the European Conference on Computer Vision (ECCV),2018

3. Harris 3d: a robust extension of the harris operator for interest point detection on 3d meshes;sipiran;The Visual Computer,2011

4. Fast Point Feature Histograms (FPFH) for 3D registration

5. Se-sync: A certifiably correct algorithm for synchronization over the special euclidean group;rosen;The International Journal of Robotics Research,2019

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