/TreeGAN

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

Primary LanguagePythonMIT LicenseMIT

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.