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+![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.