Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification
Abstract
This article presents a dataset called Paris-Lille-3D. This dataset is composed of several point clouds of outdoor scenes in Paris and Lille, France, with a total of more than 140 million hand labeled and classified points with more than 50 classes (e.g., the ground, cars and benches). This dataset is large enough and of high enough quality to further research on techniques regarding the automatic classification of urban point clouds. The fields to which that research may be applied are vast, as it provides the ability to increase productivity in regards to the management of urban infrastructures. Moreover, this type of data has the potential to be crucial in the field of autonomous vehicles.
Cite
Text
Roynard et al. "Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018. doi:10.1109/CVPRW.2018.00272Markdown
[Roynard et al. "Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.](https://mlanthology.org/cvprw/2018/roynard2018cvprw-parislille3d/) doi:10.1109/CVPRW.2018.00272BibTeX
@inproceedings{roynard2018cvprw-parislille3d,
title = {{Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification}},
author = {Roynard, Xavier and Deschaud, Jean-Emmanuel and Goulette, François},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2018},
pages = {2027-2030},
doi = {10.1109/CVPRW.2018.00272},
url = {https://mlanthology.org/cvprw/2018/roynard2018cvprw-parislille3d/}
}