44 lines
1.3 KiB
Markdown
44 lines
1.3 KiB
Markdown
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Created by Hugues THOMAS
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## Introduction
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This repository contains the implementation of **Kernel Point Convolution** (KPConv) in PyTorch. *[Work in progress]*
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KPConv is also available in [Tensorflow](https://github.com/HuguesTHOMAS/KPConv) (original implementation)
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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
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research, please consider citing:
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```
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@article{thomas2019KPConv,
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Author = {Thomas, Hugues and Qi, Charles R. and Deschaud, Jean-Emmanuel and Marcotegui, Beatriz and Goulette, Fran{\c{c}}ois and Guibas, Leonidas J.},
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Title = {KPConv: Flexible and Deformable Convolution for Point Clouds},
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Journal = {Proceedings of the IEEE International Conference on Computer Vision},
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Year = {2019}
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}
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```
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## Installation
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TODO
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## Experiments
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Currently only two experiments are available in Pytorch: classification on ModelNet40 and segmentation on S3DIS.
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TODO: Guide for runnig experiments
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TODO: More experiments
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## Acknowledgment
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Our code uses the <a href="https://github.com/jlblancoc/nanoflann">nanoflann</a> library.
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## License
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Our code is released under MIT License (see LICENSE file for details).
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## Updates
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* 31/03/2020: Initial release.
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