KPConv-PyTorch/README.md

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2020-03-31 19:56:08 +00:00
![Intro figure](https://github.com/HuguesTHOMAS/KPConv/blob/master/doc/Github_intro.png)
Created by Hugues THOMAS
## Introduction
This repository contains the implementation of **Kernel Point Convolution** (KPConv) in PyTorch. *[Work in progress]*
KPConv is also available in [Tensorflow](https://github.com/HuguesTHOMAS/KPConv) (original implementation)
KPConv is a point convolution operator presented in our ICCV2019 paper ([arXiv](https://arxiv.org/abs/1904.08889)). If you find our work useful in your
research, please consider citing:
```
@article{thomas2019KPConv,
Author = {Thomas, Hugues and Qi, Charles R. and Deschaud, Jean-Emmanuel and Marcotegui, Beatriz and Goulette, Fran{\c{c}}ois and Guibas, Leonidas J.},
Title = {KPConv: Flexible and Deformable Convolution for Point Clouds},
Journal = {Proceedings of the IEEE International Conference on Computer Vision},
Year = {2019}
}
```
## Installation
TODO
## Experiments
Currently only two experiments are available in Pytorch: classification on ModelNet40 and segmentation on S3DIS.
TODO: Guide for runnig experiments
TODO: More experiments
## Acknowledgment
Our code uses the <a href="https://github.com/jlblancoc/nanoflann">nanoflann</a> library.
## License
Our code is released under MIT License (see LICENSE file for details).
## Updates
* 31/03/2020: Initial release.