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BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

Lei Yang · Kaicheng Yu · Tao Tang · Jun Li · Kun Yuan · Li Wang · Xinyu Zhang · Peng Chen

CVPR 2023

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PyTorch Lightning Docker

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BEVHeight is a new vision-based 3D object detector specially designed for roadside scenario. BEVHeight surpasses BEVDepth base- line by a margin of 4.85% and 4.43% on DAIR-V2X-I and Rope3D benchmarks under the traditional clean settings, and by 26.88% on robust settings where external camera parameters changes. We hope our work can shed light on studying more effective feature representation on roadside perception.

News

  • [2024/05] BEVHeight is integrated into NVIDIA DeepStream-3D for sensor fusion.
  • [2023/03/15] Both arXiv and codebase are released!
  • [2023/02/27] BEVHeight got accepted to CVPR 2023!

Incoming

  • Release the pretrained models
  • Support train and test on a custom dataset

Table of Contents
  1. Getting Started
  2. Acknowledgment
  3. Citation

Getting Started

Train BEVHeight with 8 GPUs

python [EXP_PATH] --amp_backend native -b 8 --gpus 8

Eval BEVHeight with 8 GPUs

python [EXP_PATH] --ckpt_path [CKPT_PATH] -e -b 8 --gpus 8

Experimental Results

  • DAIR-V2X-I Dataset
Method Config File Range Car Pedestrain Cyclist model pth
[email protected] [email protected] [email protected]
Easy Mod. Hard Easy Mod. Hard Easy Mod. Hard
BEVHeight R50_102 [0, 102.4] 77.48 65.46 65.53 26.86 25.53 25.66 51.18 52.43 53.07 model
R50_140 [0, 140.8] 80.80 75.23 75.31 28.13 26.73 26.88 49.63 52.27 52.98 model
R101_102 [0, 102.4] 78.06 65.94 65.99 40.45 38.70 38.82 57.61 59.90 60.39 model
R101_140 [0, 140.8] 81.80 76.19 76.26 38.79 37.94 38.26 58.22 60.49 61.03 model
  • Rope3D Dataset
hom_train.pkl hom_val.pkl
Method Config File Range Car | [email protected] Big Vehicle | [email protected] Car | [email protected] Big Vehicle | [email protected] model pth
Easy Mod. Hard Easy Mod. Hard Easy Mod. Hard Easy Mod. Hard
BEVHeight R50_102 [0, 102.4] 83.49 72.46 70.17 50.73 47.81 47.80 48.12 42.45 42.34 24.58 26.25 26.28 model
R50_140 [0, 140.8] 85.46 79.15 79.06 64.38 65.75 65.77 46.39 42.85 42.71 27.21 33.99 34.03 model

Acknowledgment

This project is not possible without the following codebases.

Citation

If you use BEVHeight in your research, please cite our work by using the following BibTeX entry:

@inproceedings{yang2023bevheight,
    title={BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection},
    author={Yang, Lei and Yu, Kaicheng and Tang, Tao and Li, Jun and Yuan, Kun and Wang, Li and Zhang, Xinyu and Chen, Peng},
    booktitle={IEEE/CVF Conf.~on Computer Vision and Pattern Recognition (CVPR)},
    month = mar,
    year={2023}
}