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}
}