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Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud
[article]
2020
arXiv
pre-print
In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud. Towards this end, we encode the point cloud efficiently in a fixed radius near-neighbors graph. We design a graph neural network, named Point-GNN, to predict the category and shape of the object that each vertex in the graph belongs to. In Point-GNN, we propose an auto-registration mechanism to reduce translation variance, and also design a box merging and scoring operation to combine detections from
arXiv:2003.01251v1
fatcat:jo2mgerobnbjlmecnqhoiujjvi