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HPGNN: Using Hierarchical Graph Neural Networks for Outdoor Point Cloud Processing
[article]
2022
arXiv
pre-print
Inspired by recent improvements in point cloud processing for autonomous navigation, we focus on using hierarchical graph neural networks for processing and feature learning over large-scale outdoor LiDAR point clouds. We observe that existing GNN based methods fail to overcome challenges of scale and irregularity of points in outdoor datasets. Addressing the need to preserve structural details while learning over a larger volume efficiently, we propose Hierarchical Point Graph Neural Network
arXiv:2206.02153v1
fatcat:ijqtzzulivap7kjlnzroajuwci