Awesome
Adaptive Graph Convolution for Point Cloud Analysis
This repository contains the implementation of AdaptConv for point cloud analysis.
Adaptive Graph Convolution (AdaptConv) is a point cloud convolution operator presented in our ICCV2021 paper. If you find our work useful in your research, please cite our paper.
preprint:
@article{zhou2021adaptive,
title={Adaptive Graph Convolution for Point Cloud Analysis},
author={Zhou, Haoran and Feng, Yidan and Fang, Mingsheng and Wei, Mingqiang and Qin, Jing and Lu, Tong},
journal={arXiv preprint arXiv:2108.08035},
year={2021}
}
Installation
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The code has been tested on one configuration:
- PyTorch 1.1.0, CUDA 10.1
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Install required packages:
- numpy
- h5py
- scikit-learn
- matplotlib
Classification
Part Segmentation
Indoor Segmentation
Updates
- 09/30/2021: Updated code for part segmentation.
- 09/30/2021: Added code for S3DIS indoor segmentation.