Pointnet++ Part segmentation

This repo is implementation for PointNet++ part segmentation model based on PyTorch and pytorch_geometric.

The model has been mergered into pytorch_geometric as a point cloud segmentation example, you can try it.

Performance

Segmentation on A subset of shapenet.

Method	mcIoU	Airplane	Bag	Cap	Car	Chair	Earphone	Guitar	Knife	Lamp	Laptop	Motorbike	Mug	Pistol	Rocket	Skateboard	Table
PointNet++	81.9	82.4	79.0	87.7	77.3	90.8	71.8	91.0	85.9	83.7	95.3	71.6	94.1	81.3	58.7	76.4	82.6
PointNet++(this repo)		82.5	76.1	87.8	77.5	89.89	73.7				95.3	70.5

Note,

• mcIOU: mean per-class pIoU
• The model uses single-scale grouping with raw points as input.
• All experiments are trained with same default configration: npoints=2500, batchsize=8, num_epoches=30. The recorded accuracy above is the test accuracy of the final epoch.

Requirements

• python 3.6.8
• PyTorch 1.1.0
• pytorch_geometric 1.3.0
  • torch-cluster 1.4.2
  • torch-scatter 1.2.0
  • torch-sparse 0.4.0
• Open3D 0.6.0(optional, for visualization of segmentation result)

Usage

Training

python main.py

Show segmentation result

python vis/show_seg_res.py

Sample segmentation result

Links

• pointnet.pytorch by fxia22. This repo's tranining code is heavily borrowed from fxia22's repo.
• Official PointNet and PointNet++ tensorflow implementations
• PointNet++ classification example of pytorch_geometric library