Citation#
If you use TorchSparse, please use the following BibTeX entries to cite:
Preliminary version of TorchSparse++ (TorchSparse v2.1) is presented at CVPR Workshops 2023:
@inproceedings{tangandyang2023torchsparse++,
title = {{TorchSparse++: Efficient Point Cloud Engine}},
author = {Tang, Haotian and Yang, Shang and Liu, Zhijian and Hong, Ke and Yu, Zhongming and Li, Xiuyu and Dai, Guohao and Wang, Yu and Han, Song},
booktitle = {Computer Vision and Pattern Recognition Workshops (CVPRW)},
year = {2023}
}
TorchSparse is presented at MLSys 2022:
@inproceedings{tang2022torchsparse,
title = {{TorchSparse: Efficient Point Cloud Inference Engine}},
author = {Tang, Haotian and Liu, Zhijian and Li, Xiuyu and Lin, Yujun and Han, Song},
booktitle = {Conference on Machine Learning and Systems (MLSys)},
year = {2022}
}
Initial version of TorchSparse is part of the SPVNAS paper at ECCV 2020:
@inproceedings{tang2020searching,
title = {{Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution}},
author = {Tang, Haotian and Liu, Zhijian and Zhao, Shengyu and Lin, Yujun and Lin, Ji and Wang, Hanrui and Han, Song},
booktitle = {European Conference on Computer Vision (ECCV)},
year = {2020}
}
PCEngine paper is accepted by MLSys 2023:
@inproceedings{hong2023pcengine,
title={{Exploiting Hardware Utilization and Adaptive Dataflow for Efficient Sparse Convolution in 3D Point Clouds}},
author={Hong, Ke and Yu, Zhongming and Dai, Guohao and Yang, Xinhao and Lian, Yaoxiu and Liu, Zehao and Xu, Ningyi and Wang, Yu},
booktitle={Sixth Conference on Machine Learning and Systems (MLSys)},
year={2023}
}