Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation".

Last update: Nov 30, 2022

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Overview

FPS-Net

Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation", accepted by ISPRS journal of Photogrammetry and Remote Sensing
By Aoran Xiao, Xiaofei Yang, Shijian Lu, Dayan Guan, Jiaxing Huang

Full Paper

Install

conda create -n FPSNet python=3.7
source activate FPSNet
cd /ROOT/
pip install -r requirements.txt

Train

cd /train/tasks/semantic
sh train.sh

Inference and Test

cd /train/tasks/semantic
sh test.sh

Citation

If you use this code, please cite:

@article{xiao2021fps,
  title={FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation},
  author={Xiao, Aoran and Yang, Xiaofei and Lu, Shijian and Guan, Dayan and Huang, Jiaxing},
  journal={ISPRS Journal of Photogrammetry and Remote Sensing},
  volume={176},
  pages={237--249},
  year={2021},
  publisher={Elsevier}
}

Acknowledgement

Code borrowed heavily from lidar-bonnetal, thanks for their sharing!

Owner

Ph.D. student

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