https://gitlab.inria.fr/yixu/TransCenter_official.
TransCenter's code is now available, you can find the code and pretrained models atTransCenter: Transformers with Dense Queries for Multiple-Object Tracking
Yihong Xu, Yutong Ban, Guillaume Delorme, Chuang Gan, Daniela Rus, Xavier Alameda-Pineda
[Paper] [Project]
Bibtex
If you find this code useful, please star the project and consider citing:
@misc{xu2021transcenter,
title={TransCenter: Transformers with Dense Queries for Multiple-Object Tracking},
author={Yihong Xu and Yutong Ban and Guillaume Delorme and Chuang Gan and Daniela Rus and Xavier Alameda-Pineda},
year={2021},
eprint={2103.15145},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
Acknowledgement
The code for TransCenter is modified and network pre-trained weights are obtained from the following repositories:
- The Person Re-ID Network (./tracking/transcenter/model_zoo/ResNet_iter_25245.pth) is from Tracktor.
- The lightflownet pretrained model (./tracking/transcenter/util/LiteFlownet/network-kitti.pytorch) is from pytorch-liteflownet and LiteFlowNet.
- The deformable transformer pretrained model (./model_zoo/r50_deformable_detr-checkpoint.pth) is from Deformable-DETR.
- The data format conversion code is modified from CenterTrack.
CenterTrack, Deformable-DETR, Tracktor.
@article{zhou2020tracking,
title={Tracking Objects as Points},
author={Zhou, Xingyi and Koltun, Vladlen and Kr{\"a}henb{\"u}hl, Philipp},
journal={ECCV},
year={2020}
}
@InProceedings{tracktor_2019_ICCV,
author = {Bergmann, Philipp and Meinhardt, Tim and Leal{-}Taix{\'{e}}, Laura},
title = {Tracking Without Bells and Whistles},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}}
@article{zhu2020deformable,
title={Deformable DETR: Deformable Transformers for End-to-End Object Detection},
author={Zhu, Xizhou and Su, Weijie and Lu, Lewei and Li, Bin and Wang, Xiaogang and Dai, Jifeng},
journal={arXiv preprint arXiv:2010.04159},
year={2020}
}
Several modules are from:
MOT Metrics in Python: py-motmetrics
Soft-NMS: Soft-NMS
DETR: DETR
DCNv2: DCNv2
correlation_package: correlation_package
pytorch-liteflownet: pytorch-liteflownet
LiteFlowNet: LiteFlowNet
@InProceedings{hui18liteflownet,
author = {Tak-Wai Hui and Xiaoou Tang and Chen Change Loy},
title = {LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation},
booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018},
pages = {8981--8989},
}