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