PRBonn/lidar-bonnetal

Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving

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Converts 3D point clouds to range image representation for efficient 2D CNN-based segmentation, with multiple architecture options (SqueezeSeg, DarkNet variants) and optional CRF or k-NN post-processing refinement. Provides pre-trained models evaluated on SemanticKITTI benchmark with configurable inference pipelines for real-time autonomous driving applications.

1,028 stars. No commits in the last 6 months.

Archived Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

1,028

Forks

212

Language

Python

License

MIT

Category

lidar-point-cloud-segmentation

Last pushed

Aug 05, 2024

Commits (30d)

0

GitHub
LIDAR Point Cloud Segmentation · 24 frameworks

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