dgl/examples/pytorch/pointcloud/edgeconv

Dynamic EdgeConv

This is a reproduction of the paper Dynamic Graph CNN for Learning on Point Clouds.

The reproduced experiment is the 40-class classification on the ModelNet40 dataset. The sampled point clouds are identical to that of PointNet.

To train and test the model, simply run

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