UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking

@article{Wen2020UADETRACAN,
  title={UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking},
  author={Longyin Wen and Dawei Du and Zhaowei Cai and Zhen Lei and Ming-Ching Chang and Honggang Qi and Jongwoo Lim and Ming-Hsuan Yang and Siwei Lyu},
  journal={Comput. Vis. Image Underst.},
  year={2020},
  volume={193},
  pages={102907}
}
In recent years, numerous effective multi-object tracking (MOT) methods are developed because of the wide range of applications. Existing performance evaluations of MOT methods usually separate the object tracking step from the object detection step by using the same fixed object detection results for comparisons. In this work, we perform a comprehensive quantitative study on the effects of object detection accuracy to the overall MOT performance, using the new large-scale University at Albany… Expand
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