Model | Classification | Segmentation |
---|---|---|
PointNet | √ | √ |
PointNet ++ | √ | √ |
PointCNN | √ | √ |
DGCNN | √ | √ |
PointConv | √ | √ |
git clone this repo # 将库下载的本地
# 您需要将 ModelNet40 和 ShapeNet 数据集下载到 data_util/data/ 里面
sh train_cls.sh # 点云分类的训练和测试
sh train_seg.sh # 点云分割的训练和测试
Python 3.7
Jittor
Numpy
sklearn
lmdb
msgpack_numpy
...
Model | Input | overall accuracy |
---|---|---|
PointNet | 1024 xyz | 87.2 |
PointNet ++ | 4096 xyz + normal | 92.3 |
PointCNN | 1024 xyz | 92.6 |
DGCNN | 1024 xyz | 92.9 |
PointConv | 1024 xyz + normal | 92.4 |
Model | Speed up ratio (Compare with Pytorch) |
---|---|
PointNet | 1.22 |
PointNet ++ | 2.72 |
PointCNN | 2.41 |
DGCNN | 1.22 |
PointConv |
Model | Input | pIoU |
---|---|---|
PointNet | 2048 xyz + cls label | 83.5 |
PointNet ++ | 2048 xyz + cls label + normal | 85.0 |
PointCNN | 2048 xyz + normal | 86.0 |
DGCNN | 2048 xyz + cls label | 85.1 |
PointConv | 2048 xyz | 85.4 |
Model | Speed up ratio (Compare with Pytorch) |
---|---|
PointNet | 1.06 |
PointNet ++ | 1.85 |
PointCNN | None (No pytorch implementation) |
DGCNN | 1.05 |
PointConv | None (No pytorch implementation) |
非常欢迎您使用计图的点云库进行相关的研究,如在使用中有问题,欢迎提交 issus。