The KITTI Vision Benchmark Suite

In this work we rethink the widely used“tracking
by detection"(TBD) paradigm. We analyze several
typical tracking failure cases of existing TBD
algorithms.

To solve those failure cases, we design three
novel modules: 1) confidence-guided tracking
before detection module, 2) trajectory outlier
detection module, 3) motion-model-based trajectory
smoother.

Comprehensive experimental results on KITTI
Dataset and nuScenes Dataset shows that our final
method could achieve new SOTA results with these
plug-in modules.

alpha=0.2

@inproceedings{wang2023mot,
title={Towards Robust Reference System for
Autonomous Driving: Rethinking 3D MOT},
author={Wang, Leichen and Zhang, Jiadi and Cai, Pei
and Li, Xinrun},
booktitle={Proceedings of the 2023 IEEE
International Conference on Robotics and Automation
(ICRA)},
year={2023}
}