[2] [2] MEIMETIS D，DARAMOUSKAS I，PERIKOS I，et al. Realtime multiple object tracking using deep learning methods[J]. Neural Computing and Applications，2023，35(1)：89-118.

[4] [4] AKAN S，VARLI S. Use of deep learning in soccer videos analysis： Survey [J]. Multimedia Systems，2023，29(3)： 897-915.

[5] [5] WANG Z X，ZHENG L，LIU Y X，et al. Towards real-time multi-object tracking [C]//European Conference on Computer Vision： ECCV 2020. Glasgow： Springer International Publishing，2020： 107-122.

[6] [6] LIANG C，ZHANG Z P，ZHOU X，et al. Rethinking the competition between detection and reid in multiobject tracking [J]. IEEE Transactions on Image Processing，2022，31(1)：3182-3196.

[8] [8] ZHOU X，KOLTUN V，KRHENBHL P. Tracking objects as points[C]//European Conference on Computer Vision： ECCV 2020. Glasgow： Springer International Publishing，2020： 474-490.

[9] [9] TOKMAKOV P，LI J，BURGARD W，et al. Learning to track with object permanence [C]//Proceedings of the IEEE/CVF International Conference on Computer Vision： ICCV 2021. Montreal：IEEE Press，2021：10860-10869.

[11] [11] ZHANG Y，SUN P，JIANG Y，et al. Bytetrack： Multi -object tracking by associating every detection box [C]//European Conference on Computer Vision： ECCV 2022. Tel Aviv：Springer Nature Switzerland，2022：1-21.

[12] [12] CAO J，PANG J，WENG X，et al. Observation-centric sort： Rethinking sort for robust multi-object tracking[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recongnition： CVPR 2023. Vancouver： IEEE Press，2023：9686-9696.

[13] [13] SUN P，CAO J，JIANG Y，et al. Transtrack： Multiple object tracking with transformer[EB/OL]. arXiv Preprint，arXiv：2012. 15460，2020 (2020-12-31) [2024 - 05 - 06].https：//arxiv.org/pdf/2012.15460.

[14] [14] GAO R，WANG L. Memotr： Long-term memory-augmented transformer for multi-object tracking [C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recongnition：CVPR 2023. Vancouver： IEEE Press，2023：9901-9910.

[16] [16] KHAN S，NASEER M，HAYAT M，et al. Transformers in vision： A survey[J]. ACM Computing Surveys (CSUR)，2022，54(10s)：1-41.

[17] [17] YANG M，HAN G，YAN B，et al. Hybrid-sort： Weak cues matter for online multi-object tracking[C]//Proceedings of the AAAI Conference on Artificial Intelligence： AAAI 2024. Vancouver： AAAI Press，2024：6504-6512.

[18] [18] YANG F，ODASHIMA S，MASUI S，et al. Hard to track objects with irregular motions and similar appearances? Make it easier by buffering the matching space[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision： WACV 2023. Waikoloa： IEEE Press，2023：4799-4808.

[19] [19] CUI Y，ZENG C，ZHAO X，et al. SportsMOT： A large multi-object tracking dataset in multiple sports scenes[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recongnition： CVPR 2023. Vancouver：IEEE Press，2023：9921-9931.

[20] [20] LUITEN J，OSEP A，DENDORFER P，et al. Hota： A higher order metric for evaluating multi-object tracking[J]. International Journal of Computer Vision，2021，129：548-578.