Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classification
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... (read more)
PDFTasks
Datasets
Introduced in the Paper:
Paris-Lille-3D
Mentioned in the Paper:
ImageNet
COCO
Cityscapes
KITTI
YouTube-8M
NCLT
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods used in the Paper
| METHOD | TYPE | |
|---|---|---|
| 🤖 No Methods Found | Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet |