Lifting Multi-View Detection and Tracking to the Bird’s Eye View
Torben Teepe, Philipp Wolters, Johannes Gilg, Fabian Herzog, Gerhard Rigoll
Tip
This work is an extension of your previous work EarlyBird 🦅. Feel free to check it out and extend our multi-view object detection and tracking pipeline on other datasets!
- Install PyTorch with CUDA support
pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu118
- Install mmcv with CUDA support
pip install mmcv==2.0.0 -f https://download.openmmlab.com/mmcv/dist/cu118/torch2.1/index.html
- Install remaining dependencies
pip install -r requirements.txt
python world_track.py fit -c configs/t_fit.yml \
-c configs/d_{multiviewx,wildtrack,synthehicle}.yml \
-c configs/m_{mvdet,segnet,liftnet,bevformer}.ymlpython world_track.py test -c model_weights/config.yaml \
--ckpt model_weights/model-epoch=35-val_loss=6.50.ckpt- Simple-BEV: Adam W. Harley
- MVDeTr: Yunzhong Hou
@article{teepe2023lifting,
title={Lifting Multi-View Detection and Tracking to the Bird's Eye View},
author={Torben Teepe and Philipp Wolters and Johannes Gilg and Fabian Herzog and Gerhard Rigoll},
year={2024},
eprint={2403.12573},
archivePrefix={arXiv},
primaryClass={cs.CV}
}