peterzs / point-synthesis

Code for Point Pattern Synthesis via Irregular Convolution

Point Pattern Synthesis via Irregular Convolution

by Peihan Tu, Dani Lischinski, Hui Huang

Project page

The project page is available at https://vcc.tech/research/2019/PointSyn.

Introduction

This repository contains an implementation for Point Pattern Synthesis via Irregular Convolution. This method takes an input point pattern and generate visually similar output point pattern by optimization with a neural network. The implementation is in Python and Pytorch and Matlab.

You will need CUDA-compatible GPUs for generating results within several minutes.

If you have questions, please feel free to contact Peihan Tu ([email protected]).

Starting

The current released codes are tested on Ubuntu 16.04. To train this network properly, please install the follow dependencies:

• Python 3.6
• CUDA 8.0
• Cudnn 6.0
• Pytorch
• Numpy

Clone our repo

git clone https://github.com/tph9608/Point-Synthesis.git

Run

You can simply generate results shown in the paper by runing

./exp.sh

Please go into the results_final folder the check all of the results.

Cite

If you use our code, please cite our paper:

@article{PointSyn19,
title = {Point Pattern Synthesis via Irregular Convolution},
author = {Peihan Tu, Dani Lischinski and Hui Huang},
journal = {Computer Graphics Forum (Proceedings of SGP 2019)},
volume = {38},
number = {5},
year = {2019},
} 

License

MIT License