fb-bev
Official PyTorch implementation of FB-BEV & FB-OCC - Forward-backward view transformation for vision-centric autonomous driving perception
Science Score: 54.0%
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Repository
Official PyTorch implementation of FB-BEV & FB-OCC - Forward-backward view transformation for vision-centric autonomous driving perception
Basic Info
Statistics
- Stars: 733
- Watchers: 25
- Forks: 58
- Open Issues: 47
- Releases: 0
Topics
Metadata Files
README.md
Forward-Backward View Transformation for Vision-Centric AV Perception
Paper (FB-BEV) | Paper (FB-OCC) | Intro Video
FB-BEV and FB-OCC are a family of vision-centric 3D object detection and occupancy prediction methods based on forward-backward view transformation.
News
[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.
Getting Started
- Installation
- Prepare Dataset
- Training, Eval, Visualization
- Deployment on NVIDIA DRIVE Platform with TensorRT
Model Zoo
| Backbone | Method | Lr Schd | IoU| Config | Download | | :---: | :---: | :---: | :---: | :---: | :---: | | R50 | FB-OCC | 20ep | 39.1 |config |model|
- More model weights will be released later.
License
Copyright © 2022 - 2023, NVIDIA Corporation. All rights reserved.
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.
For business inquiries, please visit our website and submit the form: NVIDIA Research Licensing.
Citation
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}
}
Acknowledgement
Many thanks to these excellent open source projects:
Owner
- Name: NVIDIA Research Projects
- Login: NVlabs
- Kind: organization
- Website: http://research.nvidia.com
- Repositories: 166
- Profile: https://github.com/NVlabs
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - name: "MMDetection3D Contributors" title: "OpenMMLab's Next-generation Platform for General 3D Object Detection" date-released: 2020-07-23 url: "https://github.com/open-mmlab/mmdetection3d" license: Apache-2.0
GitHub Events
Total
- Issues event: 21
- Watch event: 104
- Issue comment event: 40
- Push event: 1
- Pull request event: 6
- Fork event: 17
Last Year
- Issues event: 21
- Watch event: 104
- Issue comment event: 40
- Push event: 1
- Pull request event: 6
- Fork event: 17
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 11
- Total pull requests: 2
- Average time to close issues: 3 days
- Average time to close pull requests: 26 days
- Total issue authors: 9
- Total pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 11
- Pull requests: 2
- Average time to close issues: 3 days
- Average time to close pull requests: 26 days
- Issue authors: 9
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
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- johnyang-nv (3)
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Dependencies
- docutils ==0.16.0
- m2r *
- mistune ==0.8.4
- myst-parser *
- sphinx ==4.0.2
- sphinx-copybutton *
- sphinx_markdown_tables *
- mmcv-full >=1.4.8,<=1.6.0
- mmdet >=2.24.0,<=3.0.0
- mmsegmentation >=0.20.0,<=1.0.0
- open3d *
- spconv *
- waymo-open-dataset-tf-2-1-0 ==1.2.0
- mmcv >=1.4.8
- mmdet >=2.24.0
- mmsegmentation >=0.20.1
- torch *
- torchvision *
- lyft_dataset_sdk *
- networkx >=2.2,<2.3
- numba ==0.53.0
- numpy *
- nuscenes-devkit *
- plyfile *
- scikit-image *
- tensorboard *
- trimesh >=2.35.39,<2.35.40
- asynctest * test
- codecov * test
- flake8 * test
- interrogate * test
- isort * test
- kwarray * test
- pytest * test
- pytest-cov * test
- pytest-runner * test
- ubelt * test
- xdoctest >=0.10.0 test
- yapf * test
- nvidia/cuda ${CUDA_VERSION}-cudnn8-devel-ubuntu${OS_VERSION} build