Local many-to-many matching via ROI feature decomposition for multi-object tracking-Reference-Cited by-同舟云学术

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Local many-to-many matching via ROI feature decomposition for multi-object tracking

Published:2024-06-26 Issue:10 Volume:18 Page:6573-6589
ISSN:1863-1703
Container-title:Signal, Image and Video Processing
language:en
Short-container-title:SIViP

Author:

Yang Jinlong,Ban Yandeng,Liu Jianjun

Funder

Natural Science Foundation of Jiangsu Province

Engineering Research Center of Integration and Application of Digital Learning Technology, Ministry of Education

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11760-024-03336-5.pdf

Reference46 articles.

1. Bergmann, P., Meinhardt, T., Leal-Taixé, L.: Tracking without bells and whistles. In: 2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27–November 2, 2019, pp. 941–951. IEEE (2019)

2. Boragule, A., Jang, H., Ha, N., Jeon, M.: Pixel-guided association for multi-object tracking. Sensors 22(22), 8922 (2022). https://doi.org/10.3390/s22228922

3. Brasó, G., Leal-Taixé, L.: Learning a neural solver for multiple object tracking. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, Seattle, WA, USA, June 13–19, 2020, pp. 6246–6256. Computer Vision Foundation/IEEE (2020)

4. Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J. (eds.) Computer Vision—ECCV 2020–16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part I. Lecture Notes in Computer Science, vol. 12346, pp. 213–229. Springer (2020)

5. Cetintas, O., Brasó, G., Leal-Taixé, L.: Unifying short and long-term tracking with graph hierarchies. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, BC, Canada, June 17–24, 2023, pp. 22877–22887. IEEE (2023)

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