datasets

Ruemonge428

Request data access from the VarCity 3D Semantic Segmentation Challenge website.
Download and place the folder ruemonge428 under data/. For the 3D segmentation task, make sure these 3 files are present:
- pcl.ply
- pcl_gt_train.ply
- pcl_gt_test.ply
Some post-processing (add height to the points, etc.):
```
python ruemonge428_prepare.py
```

ShapeNet Part

Download and uncompress the file from the PointNet++ repo. The link is located under the Object Part Segmentation section.
Convert to PLY files:
```
# this step can take 10~15 minutes
python shapenet_prepare.py <PATH_TO_DOWNLOADED_FOLDER>
```
Check that folder data/shapenet_ericyi_ply is now generated filled with PLY files.

References

Ruemonge428 dataset:

H. Riemenschneider, et al. Learning Where To Classify In Multi-View Semantic Segmentation. ECCV, 2014.

ShapeNet point clouds and annotations were originally collected by the authors of:

L. Yi, et al. A Scalable Active Framework for Region Annotation in 3D Shape Collections. SIGGRAPH Asia, 2016.

Normal directions of the point clouds are provided by the authors of:

C. R. Qi, et al. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space. NIPS, 2017.