TreeGAN

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

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[ Paper ]

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

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[Network]

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

For more details, refer our paper.

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[Results]

• Multi Class Generation.
  

• Single Class Generation.
  

• Single Class Interpolation.
  
  

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[Frechet Pointcloud Distance]

• This FPD version is used pretrained PointNet.

• This FPD version is for ShapeNet-Benchmark dataset from A Scalable Active Framework for Region Annotation in 3D Shape Collections.

• Our pretrained PointNet-FPD version use only subset of official ShapeNet dataset to get PointNet classification performance higher than 95%.

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[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

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[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.