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Dynamic EdgeConv
====
This is a reproduction of the paper [Dynamic Graph CNN for Learning on Point
Clouds](https://arxiv.org/pdf/1801.07829.pdf).
The reproduced experiment is the 40-class classification on the ModelNet40
dataset. The sampled point clouds are identical to that of
[PointNet](https://github.com/charlesq34/pointnet).
To train and test the model, simply run
```python
python main.py
```
The model currently takes 3 minutes to train an epoch on Tesla V100, and an
additional 17 seconds to run a validation and 20 seconds to run a test.
The best validation performance is 93.5% with a test performance of 91.8%.
## Dependencies
* `h5py`
* `tqdm`