canqin001 / ST3D

(CVPR 2021) ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

ST3D

Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021

Authors: Jihan Yang*, Shaoshuai Shi*, Zhe Wang, Hongsheng Li, Xiaojuan Qi (*equal contribution)

[arXiv] 

Overview

Our code will be coming soon.

Introduction

Our code is based on OpenPCDet v0.2. More updates on OpenPCDet are supposed to be compatible with our code.

Supported features and ToDo List

• Support inference and pre-trained model

• Support training code

Model Zoo

Installation

License

Our code is released under the Apache 2.0 license.

Acknowledgement

Our code is heavily based on OpenPCDet v0.2. Thanks OpenPCDet Development Team for their awesome codebase.

Citation

If you find this project useful in your research, please consider cite:

@inproceedings{yang2021st3d,
    title={ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection},
    author={Yang, Jihan and Shi, Shaoshuai and Wang, Zhe and Li, Hongsheng and Qi, Xiaojuan},
    booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    year={2021}
}

@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}
}