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Found 3 papers, 2 papers with code
Efficient LiDAR Point Cloud Oversegmentation Network
Then, to generate homogeneous superpoints from the sparse LiDAR point cloud, we propose a LiDAR point grouping algorithm that simultaneously considers the similarity of point embeddings and the Euclidean distance of points in 3D space.
Learning Inter-Superpoint Affinity for Weakly Supervised 3D Instance Segmentation
Due to the few annotated labels of 3D point clouds, how to learn discriminative features of point clouds to segment object instances is a challenging problem.
3D Siamese Transformer Network for Single Object Tracking on Point Clouds
Siamese network based trackers formulate 3D single object tracking as cross-correlation learning between point features of a template and a search area.
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