Awesome
PointAttN
News:Our paper has been accepted by AAAI-2024.
1. Environment setup
Install related libraries
This code has been tested on Ubuntu 20.04, python 3.8.12, torch 1.9.0 and cuda 11.2. Please install related libraries before running this code:
pip install -r requirements.txt
Compile Pytorch 3rd-party modules
please compile Pytorch 3rd-party modules ChamferDistancePytorch and mm3d_pn2. A simple way is using the following command:
cd $PointAttN_Home/utils/ChamferDistancePytorch/chamfer3D
python setup.py install
cd $PointAttN_Home/utils/mm3d_pn2
python setup.py build_ext --inplace
2. Train
Prepare training datasets
Download the datasets:
Train a model
To train the PointAttN model, modify the dataset path in cfgs/PointAttN.yaml
, run:
python train.py -c PointAttN.yaml
3. Test
Pretrained models
The pretrained models on Completion3D and PCN benchmark are available as follows:
dataset | performance | model link |
---|---|---|
Completion3D | CD = 6.63 | [BaiDuYun] (code:nf0m)[GoogleDrive] |
PCN | CD = 6.86 | [BaiDuYun] (code:kmju)[GoogleDrive] |
Test for paper result
To test PointAttN on PCN benchmark, download the pretrained model and put it into PointAttN_cd_debug_pcn
directory, run:
python test_pcn.py -c PointAttN.yaml
To test PointAttN on Completion3D benchmark, download the pretrained model and put it into PointAttN_cd_debug_c3d
directory, run:
python test_c3d.py -c PointAttN.yaml
4. Acknowledgement
-
We include the following PyTorch 3rd-party libraries:
[1] ChamferDistancePytorch
[2] mm3d_pn2 -
Some of the code of this project is borrowed from VRC-Net
5. Cite this work
If you use PointAttN in your work, please cite our paper:
@article{Wang_Cui_Guo_Li_Liu_Shen_2024,
title={PointAttN: You Only Need Attention for Point Cloud Completion},
volume={38},
url={https://ojs.aaai.org/index.php/AAAI/article/view/28356}, DOI={10.1609/aaai.v38i6.28356},
number={6},
journal={Proceedings of the AAAI Conference on Artificial Intelligence},
author={Wang, Jun and Cui, Ying and Guo, Dongyan and Li, Junxia and Liu, Qingshan and Shen, Chunhua},
year={2024},
month={Mar.},
pages={5472-5480}
}