MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving
| Autor: | Wang, Xiyang, Qi, Shouzheng, Zhao, Jieyou, Zhou, Hangning, Zhang, Siyu, Wang, Guoan, Tu, Kai, Guo, Songlin, Zhao, Jianbo, Li, Jian, Yang, Mu |
|---|---|
| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | This paper introduces MCTrack, a new 3D multi-object tracking method that achieves state-of-the-art (SOTA) performance across KITTI, nuScenes, and Waymo datasets. Addressing the gap in existing tracking paradigms, which often perform well on specific datasets but lack generalizability, MCTrack offers a unified solution. Additionally, we have standardized the format of perceptual results across various datasets, termed BaseVersion, facilitating researchers in the field of multi-object tracking (MOT) to concentrate on the core algorithmic development without the undue burden of data preprocessing. Finally, recognizing the limitations of current evaluation metrics, we propose a novel set that assesses motion information output, such as velocity and acceleration, crucial for downstream tasks. The source codes of the proposed method are available at this link: https://github.com/megvii-research/MCTrack}{https://github.com/megvii-research/MCTrack Comment: 14 pages, 7 figures |
| Databáze: | arXiv |
| Externí odkaz: |
|