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