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(CVPR 2024) CaKDP: Category-aware Knowledge Distillation and Pruning Framework for Lightweight 3D Object Detection

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CaKDP

(CVPR 2024) CaKDP: Category-aware Knowledge Distillation and Pruning Framework for Lightweight 3D Object Detection

News

[2024/3/6]: Code release for KITTI results.

Introduction

Our code is based on OpenPCDet v0.5.2 and SparseKD. More updates on OpenPCDet are supposed to be compatible with our code.

Installation

Please refer to INSTALL.md, SparseKD and OpenPCDet for the installation of OpenPCDet.

Getting Started

Please refer to GETTING_STARTED.md to learn more usage about this project.

Acknowledgement

Our code is heavily based on OpenPCDet and SparseKD. Thanks OpenPCDet Development Team and the team of SparseKD for their awesome codebase.

We also thank all reviewers and AC for their valuable comments.

Citation

@inproceedings{zhang2024cakdp,
    title={CaKDP: Category-aware Knowledge Distillation and Pruning Framework for Lightweight 3D Object Detection},
    author={Zhang, Haonan and Liu, Longjun and Huang, Yuqi and Yang, Zhao and Lei, Xinyu and Wen, Bihan},
    journal={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2024}
}
@inproceedings{yang2022towards,
    title={Towards Efficient 3D Object Detection with Knowledge Distillation},
    author={Yang, Jihan and Shi, Shaoshuai and Ding, Runyu and Wang, Zhe and Qi, Xiaojuan},
    booktitle={Advances in Neural Information Processing Systems},
    year={2022}
}
@misc{openpcdet2020,
    title={OpenPCDet: An Open-source Toolbox for 3D Object Detection from Point Clouds},
    author={OpenPCDet Development Team},
    howpublished = {\url{https://github.com/open-mmlab/OpenPCDet}},
    year={2020}
}

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