HelixNet: A Dataset for Online LiDAR Segmentation

Large-scale and open-access LiDAR dataset intended for the evaluation of real-time semantic segmentation algorithms. In contrast to other large-scale datasets, HelixNet includes fine-grained data about the sensor's rotation and position, as well as the points' release time.

You can download sequences individually or use zenodo-get to download all sequences at once:

pip install zenodo-get

zenodo-get 6519817

See companion github repository and the dedicated wepage for more information.

Cite as:

@article{loiseau22online,
title={Online Segmentation of LiDAR Sequences: Dataset and Algorithm.},
author={Romain Loiseau and Mathieu Aubry and Loic Landrieu},
journal={ECCV},
year={2022}
}

Acknowledgements :

This work was supported by ANR project READY3D ANR-19-CE23-0007.

The point cloud sequence of HelixNet was acquired during the Stereopolis II project. (N. Paparoditis et al. "Stereopolis II: A multi-purpose and multi-sensor 3D mobile mapping system for street visualisation and 3D metrology." Revue française de photogrammétrie et de télédétection, 2012)

HelixNet was annotated by FUTURMAP.

We thank Zenodo for hosting the dataset.