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A MXNet implementation for PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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// repository documentation

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# mx-pointnet(in progress)

This repository contains a [MXNet](https://github.com/apache/incubator-mxnet) implementation for the [Pointnet](https://arxiv.org/abs/1612.00593).
The official implementation is avaliable [here](https://github.com/charlesq34/pointnet).

**Note:** Only support point cloud classification Currently.

## Requirements and Dependencies

- Install MXNet(https://github.com/apache/incubator-mxnet) on a machine with CUDA GPU
- Install CUDNN v5 or v6
- Install h5py for python

## Train and Test

- Modify ```config/cfg.py``` by your setting
- ```python train.py```
- ```python test.py```

## Performance

### Classification

| Modelnet40 | Top1-Acc|
|:---:|:---:|
| Ours| 88.0 |
| Reference[1]| 89.2 |

## Reference
[1] Charles R. Qi, et al. "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593 (2016).

[2] Chen, Tianqi, et al. "Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems." arXiv:1512.01274 (2015).

[3] MXNet training code is based largely on Tusimple's resnet implementation, https://github.com/TuSimple/resnet.mxnet

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