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In the field of multi-object tracking (MOT), traditional methods often rely on the Kalman filter for motion prediction, leveraging its strengths in linear motion scenarios.
Kalman, R.E.: A new approach to linear filtering and prediction problems (1960)
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Bernardin, K., Stiefelhagen, R.: Evaluating multiple object tracking performance: The clear mot metrics. J. Image Video Process. 2008
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Bewley, A., Ge, Z., Ott, L., Ramos, F., Upcroft, B.: Simple online and realtime tracking. In: 2016 IEEE international conference on image processing (ICIP). pp. 3464–3468. IEEE (2016)
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Wu, J., Cao, J., Song, L., Wang, Y., Yang, M., Yuan, J.: Track to detect and segment: An online multi-object tracker. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 12352–12361 (2021)
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2022
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Sun, P., Cao, J., Jiang, Y., Yuan, Z., Bai, S., Kitani, K., Luo, P.: Dancetrack: Multi-object tracking in uniform appearance and diverse motion. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 20993–21002 (2022)
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Huang, H.W., Yang, C.Y., Ramkumar, S., Huang, C.I., Hwang, J.N., Kim, P.K., Lee, K., Kim, K.: Observation centric and central distance recovery for athlete tracking. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 454–460 (2023)
2023
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Seidenschwarz, J., Brasó, G., Serrano, V.C., Elezi, I., Leal-Taixé, L.: Simple cues lead to a strong multi-object tracker. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 13813–13823 (2023)
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Zeng, F., Dong, B., Zhang, Y., Wang, T., Zhang, X., Wei, Y.: Motr: End-to-end multiple-object tracking with transformer. In: European Conference on Computer Vision. pp. 659–675. Springer (2022)
2022
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Zhang, Y., Sun, P., Jiang, Y., Yu, D., Weng, F., Yuan, Z., Luo, P., Liu, W., Wang, X.: Bytetrack: Multi-object tracking by associating every detection box. In: European Conference on Computer Vision. pp. 1–21. Springer (2022)
2022
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Zhou, X., Yin, T., Koltun, V., Krähenbühl, P.: Global tracking transformers. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 8771–8780 (2022)
2022
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Cao, J., Pang, J., Weng, X., Khirodkar, R., Kitani, K.: Observation-centric sort: Rethinking sort for robust multi-object tracking. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9686–9696 (2023)
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Chai, W., Guo, X., Wang, G., Lu, Y.: Stablevideo: Text-driven consistency-aware diffusion video editing. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 23040–23050 (2023)
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2023
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Du, Y., Zhao, Z., Song, Y., Zhao, Y., Su, F., Gong, T., Meng, H.: Strongsort: Make deepsort great again. IEEE Transactions on Multimedia (2023)
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2024
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Huang, H.W., Yang, C.Y., Sun, J., Kim, P.K., Kim, K.J., Lee, K., Huang, C.I., Hwang, J.N.: Iterative scale-up expansioniou and deep features association for multi-object tracking in sports. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 163–172 (2024)
2024
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Huang, J., Wang, S., Wang, S., Wu, Z., Wang, X., Jiang, B.: Mamba-fetrack: Frame-event tracking via state space model. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV). pp. 3–18. Springer (2024)
2024
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Kuan, S.Y., Cheng, J.H., Huang, H.W., Chai, W., Yang, C.Y., Latapie, H., Liu, G., Wu, B.F., Hwang, J.N.: Boosting online 3d multi-object tracking through camera-radar cross check. In: 2024 IEEE Intelligent Vehicles Symposium (IV). pp. 2125–2132. IEEE (2024)
2024
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Song, E., Chai, W., Wang, G., Zhang, Y., Zhou, H., Wu, F., Chi, H., Guo, X., Ye, T., Zhang, Y., et al.: Moviechat: From dense token to sparse memory for long video understanding. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 18221–18232 (2024)
2024
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Sun, J., Huang, H.W., Yang, C.Y., Jiang, Z., Hwang, J.N.: Gta: Global tracklet association for multi-object tracking in sports. In: Proceedings of the Asian Conference on Computer Vision. pp. 421–434 (2024)
2024
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2024
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Xiao, C., Cao, Q., Luo, Z., Lan, L.: Mambatrack: a simple baseline for multiple object tracking with state space model. In: Proceedings of the 32nd ACM International Conference on Multimedia. pp. 4082–4091 (2024)
2024
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2024
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Yang, C.Y., Huang, H.W., Jiang, Z., Kuo, H.C., Mei, J., Huang, C.I., Hwang, J.N.: Sea you later: Metadata-guided long-term re-identification for uav-based multi-object tracking. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 805–812 (2024)
2024
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Yang, C.Y., Huang, H.W., Kim, P.K., Jiang, Z., Kim, K.J., Huang, C.I., Du, H., Hwang, J.N.: An online approach and evaluation method for tracking people across cameras in extremely long video sequence. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 7037–7045 (2024)
2024
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