wangsc1912 / Relation-Shape-CNN

Relation-Shape Convolutional Neural Network for Point Cloud Analysis (CVPR 2019 Oral & Best paper finalist)

Relation-Shape Convolutional Neural Network for Point Cloud Analysis

This repository contains the author's implementation in Pytorch for the paper:

Relation-Shape Convolutional Neural Network for Point Cloud Analysis [arXiv] [CVF]
Yongcheng Liu, Bin Fan, Shiming Xiang and Chunhong Pan
CVPR 2019 Oral & Best paper finalist     Project Page: https://yochengliu.github.io/Relation-Shape-CNN/

Citation

If our paper is helpful for your research, please consider citing:

    @inproceedings{liu2019rscnn,   
        author = {Yongcheng Liu and    
                        Bin Fan and    
                  Shiming Xiang and   
                       Chunhong Pan},   
        title = {Relation-Shape Convolutional Neural Network for Point Cloud Analysis},   
        booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},    
        pages = {8895--8904},  
        year = {2019}   
    }   

Usage: Preparation

Requirement

• Ubuntu 14.04
• Python 3 (recommend Anaconda3)
• Pytorch 0.3.*/0.4.*
• CMake > 2.8
• CUDA 8.0 + cuDNN 5.1

Building Kernel

git clone https://github.com/Yochengliu/Relation-Shape-CNN.git 
cd Relation-Shape-CNN

• mkdir build && cd build
• cmake .. && make

Dataset

Shape Classification

Download and unzip ModelNet40 (415M). Replace $data_root$ in cfgs/config_*_cls.yaml with the dataset parent path.

Usage: Training

Shape Classification

sh train_cls.sh

You can modify relation_prior in cfgs/config_*_cls.yaml.

License

The code is released under MIT License (see LICENSE file for details).

Acknowledgement

The code is heavily borrowed from Pointnet2_PyTorch.

Contact

If you have some ideas or questions about our research to share with us, please contact [e-mail]