PCT: Point Cloud Transformer

This is a Pytorch implementation of PCT: Point Cloud Transformer.

Paper link: https://arxiv.org/pdf/2012.09688.pdf

Requirements

python >= 3.7

pytorch >= 1.6

h5py

scikit-learn

and

pip install pointnet2_ops_lib/.

The code is from https://github.com/erikwijmans/Pointnet2_PyTorch https://github.com/WangYueFt/dgcnn and https://github.com/MenghaoGuo/PCT

Models

We get an accuracy of 93.2% on the ModelNet40(http://modelnet.cs.princeton.edu/) validation dataset

The path of the model is in ./checkpoints/best/models/model.t7

Example training and testing

# train
python main.py --exp_name=train --num_points=1024 --use_sgd=True --batch_size 32 --epochs 250 --lr 0.0001

# test
python main.py --exp_name=test --num_points=1024 --use_sgd=True --eval=True --model_path=checkpoints/best/models/model.t7 --test_batch_size 8

Citation

If it is helpful for your work, please cite this paper:

@misc{guo2020pct,
      title={PCT: Point Cloud Transformer}, 
      author={Meng-Hao Guo and Jun-Xiong Cai and Zheng-Ning Liu and Tai-Jiang Mu and Ralph R. Martin and Shi-Min Hu},
      year={2020},
      eprint={2012.09688},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}