{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T20:35:17Z","timestamp":1770496517784,"version":"3.49.0"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T00:00:00Z","timestamp":1700438400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T00:00:00Z","timestamp":1700438400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1007\/s11263-023-01943-2","type":"journal-article","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T17:01:53Z","timestamp":1700499713000},"page":"1443-1462","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Towards Frame Rate Agnostic Multi-object Tracking"],"prefix":"10.1007","volume":"132","author":[{"given":"Weitao","family":"Feng","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3378-7201","authenticated-orcid":false,"given":"Lei","family":"Bai","sequence":"additional","affiliation":[]},{"given":"Yongqiang","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Fengwei","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Wanli","family":"Ouyang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,20]]},"reference":[{"key":"1943_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2008\/246309","volume":"2008","author":"K Bernardin","year":"2008","unstructured":"Bernardin, K., & Stiefelhagen, R. (2008). Evaluating multiple object tracking performance: The clear mot metrics. Journal on Image and Video Processing, 2008, 1.","journal-title":"Journal on Image and Video Processing"},{"key":"1943_CR2","doi-asserted-by":"crossref","unstructured":"Bras\u00f3, G., & Leal-Taix\u00e9, L. (2020). Learning a neural solver for multiple object tracking. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (pp. 6247\u20136257).","DOI":"10.1109\/CVPR42600.2020.00628"},{"key":"1943_CR3","doi-asserted-by":"crossref","unstructured":"Chu, P., & Ling, H. (2019). Famnet: Joint learning of feature, affinity and multi-dimensional assignment for online multiple object tracking. In The IEEE International Conference on Computer Vision (ICCV).","DOI":"10.1109\/ICCV.2019.00627"},{"key":"1943_CR4","doi-asserted-by":"crossref","unstructured":"Chu, Q., Ouyang, W., Li, H., Wang, X., Liu, B., & Yu, N. (2017). Online multi-object tracking using cnn-based single object tracker with spatial-temporal attention mechanism. In ICCV.","DOI":"10.1109\/ICCV.2017.518"},{"key":"1943_CR5","doi-asserted-by":"crossref","unstructured":"Cordts, M., Omran, M., Ramos, S., Rehfeld, T. (2016). The cityscapes dataset for semantic urban scene understanding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","DOI":"10.1109\/CVPR.2016.350"},{"key":"1943_CR6","unstructured":"Dendorfer, P., Rezatofighi, H., Milan, A., Shi, J., Cremers, D., Reid,I., Roth, S., Schindler, K., & Leal-Taixe, L. (2020). Mot20: A benchmark for multi object tracking in crowded scenes. arXiv:2003.09003"},{"issue":"4","key":"1943_CR7","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1007\/s11263-020-01393-0","volume":"129","author":"P Dendorfer","year":"2021","unstructured":"Dendorfer, P., Osep, A., Milan, A., Schindler, K., Cremers, D., Reid, I., Roth, S., & Leal-Taixe, L. (2021). Motchallenge: A benchmark for single-camera multiple target tracking. International Journal of Computer Vision, 129(4), 845\u2013881.","journal-title":"International Journal of Computer Vision"},{"key":"1943_CR8","unstructured":"Ge, Z., Liu, S., Wang, F., Li, Z., & Sun, J. (2021). YOLOX: Exceeding YOLO series in 2021. https:\/\/arxiv.org\/abs\/2107.08430."},{"key":"1943_CR9","doi-asserted-by":"crossref","unstructured":"Han, T., Bai, L., Gao, J., Wang, Q., & Ouyang, W. (2022). Dr. vic: Decomposition and reasoning for video individual counting. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (pp. 3083\u20133092).","DOI":"10.1109\/CVPR52688.2022.00309"},{"key":"1943_CR10","unstructured":"Hornakova, A., Henschel, R., Rosenhahn, B., & Swoboda, P. (2020). Lifted disjoint paths with application in multiple object tracking. In International conference on machine learning, PMLR (pp. 4364\u20134375)."},{"issue":"2","key":"1943_CR11","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1007\/s11263-019-01231-y","volume":"128","author":"W Hu","year":"2020","unstructured":"Hu, W., Shi, X., Zhou, Z., & Xing, J. (2020). Dual l1-normalized context aware tensor power iteration and its applications to multi-object tracking and multi-graph matching. International Journal of Computer Vision, 128(2), 360\u2013392.","journal-title":"International Journal of Computer Vision"},{"key":"1943_CR12","doi-asserted-by":"crossref","unstructured":"Kieritz, H., Hubner, W., & Arens, M. (2018). Joint detection and online multi-object tracking. In CVPRW.","DOI":"10.1109\/CVPRW.2018.00195"},{"key":"1943_CR13","doi-asserted-by":"crossref","unstructured":"Li, J., Gao, X., & Jiang, T. (2020). Graph networks for multiple object tracking. In Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (pp. 719\u2013728).","DOI":"10.1109\/WACV45572.2020.9093347"},{"key":"1943_CR14","unstructured":"Lin, W., Liu, H., Liu, S., Li, Y., Qian, R., Wang, T., Xu, N., Xiong, H., Qi, G.-J. & Sebe, N. (2020). Human in events: A large-scale benchmark for human-centric video analysis in complex events. arXiv:2005.04490"},{"issue":"2","key":"1943_CR15","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1007\/s11263-020-01375-2","volume":"129","author":"J Luiten","year":"2021","unstructured":"Luiten, J., Osep, A., Dendorfer, P., Torr, P., Geiger, A., Leal-Taixe, L., & Leibe, B. (2021). Hota: A higher order metric for evaluating multi-object tracking. International Journal of Computer Vision, 129(2), 548\u2013578.","journal-title":"International Journal of Computer Vision"},{"issue":"12","key":"1943_CR16","doi-asserted-by":"publisher","first-page":"3255","DOI":"10.1007\/s11263-021-01527-y","volume":"129","author":"C Ma","year":"2021","unstructured":"Ma, C., Yang, F., Li, Y., Jia, H., Xie, X., & Gao, W. (2021). Deep trajectory post-processing and position projection for single & multiple camera multiple object tracking. International Journal of Computer Vision, 129(12), 3255\u20133278.","journal-title":"International Journal of Computer Vision"},{"key":"1943_CR17","doi-asserted-by":"crossref","unstructured":"Maksai, A., & Fua, P. (2019). Eliminating exposure bias and metric mismatch in multiple object tracking. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (pp. 4639\u20134648).","DOI":"10.1109\/CVPR.2019.00477"},{"key":"1943_CR18","unstructured":"Milan, A., Leal-Taix\u00e9, L., & Reid, I., Roth, S., & Schindler, K. (2016). MOT16: A benchmark for multi-object tracking. arXiv:1603.00831"},{"key":"1943_CR19","doi-asserted-by":"crossref","unstructured":"Milan, A., Rezatofighi, S. H., Dick, A. R., Reid,. I., & Schindler, K. (2017). Online multi-target tracking using recurrent neural networks. In AAAI.","DOI":"10.1609\/aaai.v31i1.11194"},{"key":"1943_CR20","doi-asserted-by":"crossref","unstructured":"Ristani, E., Solera, F., Zou, R., Cucchiara, R., & Tomasi, C. (2016). Performance measures and a data set for multi-target, multi-camera tracking. In European Conference on Computer Vision (pp. 17\u201335). Springer.","DOI":"10.1007\/978-3-319-48881-3_2"},{"key":"1943_CR21","doi-asserted-by":"crossref","unstructured":"Sadeghian, A., Alahi, A., & Savarese, S. (2017). Tracking the untrackable: Learning to track multiple cues with long-term dependencies. In ICCV.","DOI":"10.1109\/ICCV.2017.41"},{"key":"1943_CR22","doi-asserted-by":"crossref","unstructured":"Saleh, F., Aliakbarian, S., Rezatofighi, H., & Salzmann, M. (2021). Probabilistic tracklet scoring and inpainting for multiple object tracking. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (pp. 14329\u201314339).","DOI":"10.1109\/CVPR46437.2021.01410"},{"key":"1943_CR23","unstructured":"Shao, S., Zhao, Z., Li, B., Xiao, T., Yu, G., Zhang, X., & Sun, J. (2018). Crowdhuman: A benchmark for detecting human in a crowd. arXiv:1805.00123"},{"key":"1943_CR24","doi-asserted-by":"crossref","unstructured":"Simsek, F. E., Cigla, C., & Kayabol, K. (2023). Sompt22: A surveillance oriented multi-pedestrian tracking dataset. In Computer Vision\u2013ECCV 2022 Workshops: Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part V (pp. 659\u2013675). Springer.","DOI":"10.1007\/978-3-031-25072-9_44"},{"key":"1943_CR25","doi-asserted-by":"crossref","unstructured":"Takala, V., & Pietikainen, M. (2007). Multi-object tracking using color, texture and motion. In 2007 IEEE Conference on Computer Vision and Pattern Recognition, IEEE (pp. 1\u20137).","DOI":"10.1109\/CVPR.2007.383506"},{"key":"1943_CR26","doi-asserted-by":"crossref","unstructured":"Tang, S., Andres, B., Andriluka, M., & Schiele, B. (2016). Multi-person tracking by multicut and deep matching. In ECCV.","DOI":"10.1007\/978-3-319-48881-3_8"},{"key":"1943_CR27","doi-asserted-by":"crossref","unstructured":"Tang, S., Andriluka, M., Andres, B., & Schiele, B. (2017). Multiple people tracking by lifted multicut and person reidentification. In CVPR.","DOI":"10.1109\/CVPR.2017.394"},{"key":"1943_CR28","doi-asserted-by":"crossref","unstructured":"Wang, Y., Kitani, K., & Weng, X. (2021). Joint object detection and multi-object tracking with graph neural networks. In 2021 IEEE International Conference on Robotics and Automation (ICRA), IEEE (pp. 13708\u201313715).","DOI":"10.1109\/ICRA48506.2021.9561110"},{"issue":"2","key":"1943_CR29","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1007\/s11263-016-0943-0","volume":"122","author":"L Wen","year":"2017","unstructured":"Wen, L., Lei, Z., Chang, M. C., Qi, H., & Lyu, S. (2017). Multi-camera multi-target tracking with space-time-view hyper-graph. International Journal of Computer Vision, 122(2), 313\u2013333.","journal-title":"International Journal of Computer Vision"},{"key":"1943_CR30","doi-asserted-by":"crossref","unstructured":"Wojke, N., Bewley, A., & Paulus, D. (2017). Simple online and realtime tracking with a deep association metric. In ICIP.","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"1943_CR31","doi-asserted-by":"crossref","unstructured":"Wu, J., Cao, J., & Song, L., Wang, Y., Yang, M., & Yuan, J. (2021). 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\u201312361).","DOI":"10.1109\/CVPR46437.2021.01217"},{"key":"1943_CR32","doi-asserted-by":"crossref","unstructured":"Xu, J., Cao, Y., Zhang, Z., & Hu, H. (2019). Spatial-temporal relation networks for multi-object tracking. In ICCV.","DOI":"10.1109\/ICCV.2019.00409"},{"issue":"1","key":"1943_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11263-018-1087-1","volume":"127","author":"JH Yoon","year":"2019","unstructured":"Yoon, J. H., Lee, C. R., Yang, M. H., & Yoon, K.-J. (2019). Structural constraint data association for online multi-object tracking. International Journal of Computer Vision, 127(1), 1\u201321.","journal-title":"International Journal of Computer Vision"},{"key":"1943_CR34","doi-asserted-by":"crossref","unstructured":"Yu, F., Li, W., Li, Q., Liu, Y, Shi, X., & Yan, J. (2016). Poi: Multiple object tracking with high performance detection and appearance feature. In ECCV.","DOI":"10.1007\/978-3-319-48881-3_3"},{"key":"1943_CR35","doi-asserted-by":"crossref","unstructured":"Zhang, L., Li, Y., & Nevatia, R. (2008). Global data association for multi-object tracking using network flows. In CVPr.","DOI":"10.1109\/CVPR.2008.4587584"},{"issue":"11","key":"1943_CR36","doi-asserted-by":"publisher","first-page":"3069","DOI":"10.1007\/s11263-021-01513-4","volume":"129","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Wang, C., Wang, X., Zend, W., & Liu, W. (2021). Fairmot: On the fairness of detection and re-identification in multiple object tracking. International Journal of Computer Vision, 129(11), 3069\u20133087.","journal-title":"International Journal of Computer Vision"},{"key":"1943_CR37","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Sun, P., Jiang, Y., Yu, D., Weng, F., Yuan, Z., Luo, P., Liu, W., & Wang, X. (2022). Bytetrack: Multi-object tracking by associating every detection box. In Proceedings of the European Conference on Computer Vision (ECCV).","DOI":"10.1007\/978-3-031-20047-2_1"},{"key":"1943_CR38","doi-asserted-by":"crossref","unstructured":"Zhou, X., Koltun, V., & Kr\u00e4henb\u00fchl, P. (2020). Tracking objects as points. ECCV.","DOI":"10.1007\/978-3-030-58548-8_28"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-023-01943-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-023-01943-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-023-01943-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T08:07:55Z","timestamp":1715069275000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-023-01943-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,20]]},"references-count":38,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["1943"],"URL":"https:\/\/doi.org\/10.1007\/s11263-023-01943-2","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,20]]},"assertion":[{"value":"9 August 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}