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[Neural Computing and Applications 2024] Fast Point Completion Network

FPCN 최신버젼 다운로드

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// repository documentation

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## Fast Point Completion Network
This is the official PyTorch implementation of [Fast Point Completion Network](https://link.springer.com/article/10.1007/s00521-024-09624-y) (Neural Computing and Applications 2024).

![image](https://github.com/doldolOuO/FPCN/blob/main/FPCN.png)

## Cite this work

```
@article{fang2024fpcn,
  title={Fast Point Completion Network},
  author={Fang, Chenghao and 
          Yang, Bing and 
          Ye, Hailiang and 
          Cao, Feilong},
  journal={Neural Computing and Applications},
  year={2024},
  volume={36},
  pages={10897-10913},
  doi={https://doi.org/10.1007/s00521-024-09624-y}
}
```

## Datasets

We use the [ShapeNet](https://www.shapenet.org/) and [KITTI](http://www.cvlibs.net/datasets/kitti/) datasets in our experiments, which are available below:
- [ShapeNet](https://drive.google.com/drive/folders/1P_W1tz5Q4ZLapUifuOE4rFAZp6L1XTJz)
- [KITTI](https://drive.google.com/drive/folders/1fSu0_huWhticAlzLh3Ejpg8zxzqO1z-F)

## Acknowledgements
Some of the code of this repo is borrowed from:

- [GRNet](https://github.com/hzxie/GRNet)

- [ChamferDistance](https://github.com/ThibaultGROUEIX/ChamferDistancePytorch)

- [EMD](https://github.com/Colin97/MSN-Point-Cloud-Completion/tree/master/emd)

- [PointNet++](https://github.com/erikwijmans/Pointnet2_PyTorch)

## License
This project is open sourced under MIT license.

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