International audienceThis 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 avail...
To reduce the cost of manually annotating training data for supervised classifiers, we propose an au...
International audienceThe object of the TerraMobilita/iQmulus 3D urban analysis benchmark is to eval...
3D urban maps with semantic labels and metric information are not only essential for the next genera...
International audienceThis paper introduces a new Urban Point Cloud Dataset for Automatic Segmentati...
Abstract: This paper describes a publicly available 3D database from the rue Madame, a street in the...
International audienceThis article presents a dataset called Paris-Lille-3D. This dataset is compose...
International audienceThis paper describes a publicly available 3D database from the rue Madame, a s...
This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds...
An essential prerequisite for unleashing the potential of supervised deep learning algorithms in the...
This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds...
The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (ML...
It is fundamental for 3D city maps to efficiently classify objects of point clouds in urban scenes. ...
It is fundamental for 3D city maps to efficiently classify objects of point clouds in urban scenes. ...
Segmentation and classification of urban range data into different object classes have several chall...
Mobile laser scanning (MLS) is a modern and powerful technology capable of obtaining massive point c...
To reduce the cost of manually annotating training data for supervised classifiers, we propose an au...
International audienceThe object of the TerraMobilita/iQmulus 3D urban analysis benchmark is to eval...
3D urban maps with semantic labels and metric information are not only essential for the next genera...
International audienceThis paper introduces a new Urban Point Cloud Dataset for Automatic Segmentati...
Abstract: This paper describes a publicly available 3D database from the rue Madame, a street in the...
International audienceThis article presents a dataset called Paris-Lille-3D. This dataset is compose...
International audienceThis paper describes a publicly available 3D database from the rue Madame, a s...
This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds...
An essential prerequisite for unleashing the potential of supervised deep learning algorithms in the...
This paper presents our work on automated classification of Mobile Laser Scanning (MLS) point clouds...
The demand for 3D maps of cities and road networks is steadily growing and mobile laser scanning (ML...
It is fundamental for 3D city maps to efficiently classify objects of point clouds in urban scenes. ...
It is fundamental for 3D city maps to efficiently classify objects of point clouds in urban scenes. ...
Segmentation and classification of urban range data into different object classes have several chall...
Mobile laser scanning (MLS) is a modern and powerful technology capable of obtaining massive point c...
To reduce the cost of manually annotating training data for supervised classifiers, we propose an au...
International audienceThe object of the TerraMobilita/iQmulus 3D urban analysis benchmark is to eval...
3D urban maps with semantic labels and metric information are not only essential for the next genera...