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Person-MinkUNet. Winner of JRDB 3D detection challenge in JRDB-ACT Workshop at CVPR 2021. https://arxiv.org/abs/2107.06780

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Person-MinkUNet

PyTorch implementation of Person-MinkUNet. Winner of JRDB 3D detection challenge in JRDB-ACT Workshop at CVPR 2021 [arXiv] [video] [leaderboard].

Prerequisite

  • python>=3.8
  • torchsparse==1.2.0 (link)
  • PyTorch==1.6.0

Quick start

Download JackRabbot dataset under PROJECT/data/JRDB.

# install lidar_det project
python setup.py develop

# build libraries
cd lib/iou3d
python setup.py develop

cd ../jrdb_det3d_eval
python setup.py develop

Run

python bin/train.py --cfg PATH_TO_CFG [--ckpt PATH_TO_CKPT] [--evaluation]

Model zoo

Split Checkpoint Config
train ckpt cfg
train + val ckpt cfg

Acknowledgement

Citation

@inproceedings{Jia2021PersonMinkUnet,
  title        = {{Person-MinkUNet: 3D Person Detection with LiDAR Point Cloud}},
  author       = {Dan Jia and Bastian Leibe},
  booktitle    = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year         = {2021}
}

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Person-MinkUNet. Winner of JRDB 3D detection challenge in JRDB-ACT Workshop at CVPR 2021. https://arxiv.org/abs/2107.06780

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