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3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions

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TreeGAN


This repository TreeGAN is for 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions paper accepted on ICCV 2019


[ Paper ]

3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions
(Dong Wook Shu*, Sung Woo Park*, Junseok Kwon)


[Network]

TreeGAN network consists of "TreeGCN Generator" and "Discriminator".

For more details, refer our paper.


[Results]

  • Multi Class Generation.
    Multi-class

  • Single Class Generation.
    Single-class

  • Single Class Interpolation.
    Plane-class Interpolation
    Chair-class Interpolation


[Frechet Pointcloud Distance]


[Citing]

inproceedings{~~, title={}, author={}, year={2019} }

[Setting]

This project was tested on Windows 10 / Ubuntu 16.04 Using conda install command is recommended to setting.

Packages

  • Python 3.6
  • Numpy
  • Pytorch 1.0
  • visdom

[Arguments]

In our project, arguments.py file has almost every parameters to specify for training.

For example, if you want to train, it needs to specify dataset_path argument.

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3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions

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