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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.

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Geometry Sharing Network for 3D Point Cloud Classification and Segmentation

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