point2color

Point2color: 3D Point Cloud Colorization Using a Conditional Generative Network and Differentiable Rendering for Airborne LiDAR Earth Vision 2021

Papaer
Project

Environment

The following libraries are the environment I used for my experiments.

• python 3.6.5
• cuda: 10.1
• nccl: 2.2.13
• cudnn: 7.4
• librarys
  • laspy==1.7.0
  • torch==1.6.0+cu101
  • torch-cluster==1.5.8
  • torch-geometric==1.6.3
  • torch-scatter==2.0.5
  • torch-sparse==0.6.8
  • torch-spline-conv==1.2.0
  • torchfile==0.1.0
  • torchvision==0.7.0+cu101
  • pytorch3d==0.3.0
  • open3d==0.8.0.0

@InProceedings{Shinohara_2021_CVPR,
author = {Shinohara, Takayuki and Xiu, Haoyi and Matsuoka, Masashi},
title = {Point2color: 3D Point Cloud Colorization Using a Conditional Generative Network and Differentiable Rendering for Airborne LiDAR},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2021},
pages = {1062-1071}
}