GS-Net
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Geometry Sharing Network for 3D Point Cloud Classification and Segmentation
Geometry Sharing Network for 3D Point Cloud Classification and Segmentation. AAAI 2020
Mingye Xu, Zhipeng Zhou, Yu Qiao.
Overview
Futher information please contact Mingye Xu ([email protected])
Citation
Please cite this paper if you want to use it in your work,
@misc{xu2019geometry,
title={Geometry Sharing Network for 3D Point Cloud Classification and Segmentation},
author={Mingye Xu and Zhipeng Zhou and Yu Qiao},
year={2019},
eprint={1912.10644},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
Installation
Requirements
- Linux (tested on Ubuntu 14.04/16.04)
- Python 3.5+
- PyTorch 1.0
Install
Install this library by running the following command:
cd OP
python setup.py install
cd ../
Usage
Point Cloud Classification
- Run the training script:
python main.py
- Run the evaluation script :
python main.py --eval True --model_path 'pretrained/model_1024_92.9.t7'
Other information
We will release part segmentation code later. Due to the differences of models, please contact us by email if you need the classification model(2048 input points) with 93.3% accuracy.
Acknowledgement
This code is based on DGCNN and Pointnet2.Pytorch.