FB-BEV and FB-OCC are a family of vision-centric 3D object detection and occupancy prediction methods based on forward-backward view transformation.

• [2023/8/01] FB-BEV was accepted to ICCV 2023.
• 🏆 [2023/6/16] FB-OCC wins both Outstanding Champion and Innovation Award in Autonomous Driving Challenge in conjunction with CVPR 2023 End-to-End Autonomous Driving Workshop and Vision-Centric Autonomous Driving Workshop.

• Installation
• Prepare Dataset
• Training, Eval, Visualization

• More model weights will be released later.

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This work is made available under the Nvidia Source Code License-NC. Click here to view a copy of this license.

The pre-trained models are shared under CC-BY-NC-SA-4.0. If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

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If this work is helpful for your research, please consider citing:

@inproceedings{li2023fbbev,
  title={{FB-BEV}: {BEV} Representation from Forward-Backward View Transformations},
  author={Li, Zhiqi and Yu, Zhiding and Wang, Wenhai and Anandkumar, Anima and Lu, Tong and Alvarez, Jose M},
  booktitle={IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2023}
}

@article{li2023fbocc,
  title={{FB-OCC}: {3D} Occupancy Prediction based on Forward-Backward View Transformation},
  author={Li, Zhiqi and Yu, Zhiding and Austin, David and Fang, Mingsheng and Lan, Shiyi and Kautz, Jan and Alvarez, Jose M},
  journal={arXiv:2307.01492},
  year={2023}
}

Many thanks to these excellent open source projects:

• BEVFormer, BEVDet, Occ3D, OpenOccupancy, SoloFusion