  This paper introduces a new Urban Point Cloud Dataset for Automatic
Segmentation and Classification acquired by Mobile Laser Scanning (MLS). We
describe how the dataset is obtained from acquisition to post-processing and
labeling. This dataset can be used to learn classification algorithm, however,
given that a great attention has been paid to the split between the different
objects, this dataset can also be used to learn the segmentation. The dataset
consists of around 2km of MLS point cloud acquired in two cities. The number of
points and range of classes make us consider that it can be used to train
Deep-Learning methods. Besides we show some results of automatic segmentation
and classification. The dataset is available at:
http://caor-mines-paristech.fr/fr/paris-lille-3d-dataset/
