1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking

Yu Wang; Sijia Chen; Li Huang; Runzhou Ge; Yihan Hu; Zhuangzhuang Ding; Jie Liao

1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking

Computer Vision and Pattern Recognition 2020-06-30 v1

Authors: Yu Wang , Sijia Chen , Li Huang , Runzhou Ge , Yihan Hu , Zhuangzhuang Ding , Jie Liao

Abstract

This technical report presents the online and real-time 2D and 3D multi-object tracking (MOT) algorithms that reached the 1st places on both Waymo Open Dataset 2D tracking and 3D tracking challenges. An efficient and pragmatic online tracking-by-detection framework named HorizonMOT is proposed for camera-based 2D tracking in the image space and LiDAR-based 3D tracking in the 3D world space. Within the tracking-by-detection paradigm, our trackers leverage our high-performing detectors used in the 2D/3D detection challenges and achieved 45.13% 2D MOTA/L2 and 63.45% 3D MOTA/L2 in the 2D/3D tracking challenges.

Keywords

multi-object tracking object detection image processing competition

Cite

@article{arxiv.2006.15506,
  title  = {1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking},
  author = {Yu Wang and Sijia Chen and Li Huang and Runzhou Ge and Yihan Hu and Zhuangzhuang Ding and Jie Liao},
  journal= {arXiv preprint arXiv:2006.15506},
  year   = {2020}
}

1st Place Solutions for Waymo Open Dataset Challenges -- 2D and 3D Tracking

Abstract

Keywords

Cite

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