Distill Bev Save

DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation

Zeyu Wang, Dingwen Li, Chenxu Luo, Cihang Xie, Xiaodong Yang
DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation, ICCV 2023

Get Started

Installtion

Please refer to INSTALL to set up the environment and install the dependencies (see more details in Dockerfile).

Data Preparation

Please follow the instructions in DATA.

Training and Evaluation

Please follow the instructions in RUN.

Main Results

BEVDepth and BEVFormer are respectively used in this repo as CNNs and Transformers based students to exemplify the improvement by DistillBEV.

• Backbone: ResNet-50 pre-trained on ImageNet-1K

• Backbone: ResNet-101 pre-trained on ImageNet-1K

Citation

Please cite the following paper if this repo helps your research:

@InProceedings{Wang_2023_ICCV,
    author    = {Wang, Zeyu and Li, Dingwen and Luo, Chenxu and Xie, Cihang and Yang, Xiaodong},
    title     = {DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation},
    booktitle = {IEEE/CVF International Conference on Computer Vision (ICCV)},
    year      = {2023},
}

Acknowledgement

We thank the authors for the multiple great open-sourced repos, including MMDetection3D, CenterPoint, BEVDet, BEVDepth and BEVFormer.

License

Copyright (C) 2023 QCraft. All rights reserved. Licensed under the CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike 4.0 International). The code is released for academic research use only. For commercial use, please contact [email protected].