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References

1 
Y. Zhang, P. Sun, Y. Jiang, D. Yu, F. Weng, Z. Yuan, P. Luo, W. Liu, X. Wang, 2022, ByteTack: Multi-object Tracking by Association Every Detection Box, in Proceedings of the European conference on computer vision (ECCV), pp. 1-21Google Search
2 
N. Aharon, R. Orfaig, B. Borbrovsky, 2022, BoT-SORT: Robust Associations Multi-Pedestrian Tracking, arXiv preprint arXiv:2206.14651Google Search
3 
Y. Zhang, C. Wang, X. Wang, 2021, FairMOT: On the Fairness of Detection and Re-identification in Multiple Object Tracking, International Journal of Computer Vision, pp. 3069-3087Google Search
4 
E. Yu, Z. Li, S. Han, 2022, Towards Discriminative Representation: Multi-view Trajectory Contrastive Learning for Online Multi-object Tracking, in Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 8834-8843Google Search
5 
Z. Ge, S. Liu, F. Wang, Z. Li, J. Sun, 2021, YOLOX: Exceeding YOLO Series in 2021, arXiv preprint arXiv:2107.08430Google Search
6 
X. Zhou, D. Wang, P. Krähenbühl, 2019, Objects as points, arXiv preprint arXiv:1904.07850Google Search
7 
T. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, S. Belongie, 2017, Feature Pyramid Networks for Object Detection, in Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 2117-2125Google Search
8 
S. Malla, B. Dariush, C. Choi, 2020, TITAN: Future Forecast Using Action Priors, in Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 11186-11196Google Search
9 
K. Bernardin, R. Stiefelhagen, 2008, Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics, EURASIP Journal on Image and Video Processing, pp. 1-10Google Search
10 
E. Ristani, F. Solera, R. S. Zou, R. Cucchiara, C. Tomasi, 2016, Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking, in Proceedings of the European conference on computer vision (ECCV), pp. 17-35Google Search
11 
A. Bochkovskiy, C. Wang, H. M. Liao, 2020, YOLOv4: Optimal Speed and Accuracy of Object Detection, arXiv preprint arXiv:2004.10934Google Search
12 
S. Liu, L. Qi, H. Qin, J. Shi, J. Jia, 2018, Path Aggregation Network for Instance Segmentation, in Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 8759-8768Google Search
13 
T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, C. L. Zitnick, 2014, Microsoft COCO: Common Objects in Context, in Proceedings of the European conference on computer vision (ECCV), pp. 740-755Google Search