Dataset Open Access

HelixNet: A Dataset for Online LiDAR Segmentation

Loiseau Romain; Aubry Mathieu; Landrieu Loïc

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.
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