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Found 3 papers, 2 papers with code
End-to-End 3D Point Cloud Learning for Registration Task Using Virtual Correspondences
3D Point cloud registration is still a very challenging topic due to the difficulty in finding the rigid transformation between two point clouds with partial correspondences, and it's even harder in the absence of any initial estimation information.
SeqLPD: Sequence Matching Enhanced Loop-Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles
Place recognition and loop-closure detection are main challenges in the localization, mapping and navigation tasks of self-driving vehicles.
LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis
Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and it's even harder in the large-scale dynamic environments.
Ranked #5 on
3D Place Recognition
on CS-Campus3D
