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Motion-based association for Multi-Object Tracking (MOT) has recently re-achieved prominence with the rise of powerful object detectors.
“Contributions to the theory of optimal control,”
Rudolf Emil Kalman et al., · 1960
Earlier work this paper cites.
“Evaluating multiple object tracking performance: the clear mot metrics,”
Keni Bernardin and Rainer Stiefelhagen, · 2008
Earlier work this paper cites.
“Mot16: A benchmark for multi-object tracking,”
Anton Milan, Laura Leal-Taixé, Ian Reid, Stefan Roth, and Konrad Schindler, · 2016
Earlier work this paper cites.
“Simple online and realtime tracking,”
Alex Bewley, Zongyuan Ge, Lionel Ott, Fabio Ramos, and Ben Upcroft, · 2016
Earlier work this paper cites.
“Simple online and realtime tracking with a deep association metric,”
Nicolai Wojke, Alex Bewley, and Dietrich Paulus, · 2017
Earlier work this paper cites.
“Attention is all you need,”
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin, · 2017
Earlier work this paper cites.
“Mot20: A benchmark for multi object tracking in crowded scenes,”
Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian Reid, Stefan Roth, Konrad Schindler, and Laura Leal-Taixé, · 2020
Earlier work this paper cites.
“Transtrack: Multiple object tracking with transformer,”
Peize Sun, Jinkun Cao, Yi Jiang, Rufeng Zhang, Enze Xie, Zehuan Yuan, Changhu Wang, and Ping Luo, · 2020
Earlier work this paper cites.
“Rethinking the competition between detection and reid in multi-object tracking,”
Chao Liang, Zhipeng Zhang, Yi Lu, Xue Zhou, Bing Li, Xiyong Ye, and Jianxiao Zou, · 2020
Earlier work this paper cites.
“Tracking objects as points,”
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl, · 2020
Earlier work this paper cites.
“MMTracking: OpenMMLab video perception toolbox and benchmark,” https://github.com/open-mmlab/mmtracking , 2020
MMTracking Contributors, · 2020
Cited alongside, same era.
“Fastreid: A pytorch toolbox for general instance re-identification,”
Lingxiao He, Xingyu Liao, Wu Liu, Xinchen Liu, Peng Cheng, and Tao Mei, · 2020
Cited alongside, same era.
“Bytetrack: Multi-object tracking by associating every detection box,”
Yifu Zhang, Peize Sun, Yi Jiang, Dongdong Yu, Zehuan Yuan, Ping Luo, Wenyu Liu, and Xinggang Wang, · 2021
Cited alongside, same era.
“Dancetrack: Multi-object tracking in uniform appearance and diverse motion,”
Peize Sun, Jinkun Cao, Yi Jiang, Zehuan Yuan, Song Bai, Kris Kitani, and Ping Luo, · 2021
Cited alongside, same era.
“Fairmot: On the fairness of detection and re-identification in multiple object tracking,”
“Transmot: Spatial-temporal graph transformer for multiple object tracking,”
Peng Chu, Jiang Wang, Quanzeng You, Haibin Ling, and Zicheng Liu, · 2021
Later among the works it cites.
“Semi-tcl: Semi-supervised track contrastive representation learning,”
Wei Li, Yuanjun Xiong, Shuo Yang, Mingze Xu, Yongxin Wang, and Wei Xia, · 2021
Later among the works it cites.
“Joint object detection and multi-object tracking with graph neural networks,”
Yongxin Wang, Kris Kitani, and Xinshuo Weng, · 2021
Later among the works it cites.
“Track to detect and segment: An online multi-object tracker,”
Jialian Wu, Jiale Cao, Liangchen Song, Yu Wang, Ming Yang, and Junsong Yuan, · 2021
Later among the works it cites.
“Hota: A higher order metric for evaluating multi-object tracking,”
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer, Philip Torr, Andreas Geiger, Laura Leal-Taixé, and Bastian Leibe, · 2021
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Yifu Zhang, Chunyu Wang, Xinggang Wang, Wenjun Zeng, and Wenyu Liu, · 2021
Cited alongside, same era.
“Quasi-dense similarity learning for multiple object tracking,”
Jiangmiao Pang, Linlu Qiu, Xia Li, Haofeng Chen, Qi Li, Trevor Darrell, and Fisher Yu, · 2021
Cited alongside, same era.
“Motr: End-to-end multiple-object tracking with transformer,”
Fangao Zeng, Bin Dong, Tiancai Wang, Xiangyu Zhang, and Yichen Wei, · 2021
Cited alongside, same era.
“Trackformer: Multi-object tracking with transformers,”
Tim Meinhardt, Alexander Kirillov, Laura Leal-Taixe, and Christoph Feichtenhofer, · 2021
Cited alongside, same era.
“Transcenter: Transformers with dense queries for multiple-object tracking,”
Yihong Xu, Yutong Ban, Guillaume Delorme, Chuang Gan, Daniela Rus, and Xavier Alameda-Pineda, · 2021
Cited alongside, same era.
“A general recurrent tracking framework without real data,”
Shuai Wang, Hao Sheng, Yang Zhang, Yubin Wu, and Zhang Xiong, · 2021
Cited alongside, same era.
Later among the works it cites.
“Observation-centric sort: Rethinking sort for robust multi-object tracking,”
Jinkun Cao, Xinshuo Weng, Rawal Khirodkar, Jiangmiao Pang, and Kris Kitani, · 2022
Later among the works it cites.
“Bot-sort: Robust associations multi-pedestrian tracking,” 2022
Nir Aharon, Roy Orfaig, and Ben-Zion Bobrovsky, · 2022
Later among the works it cites.
“Track targets by dense spatio-temporal position encoding,”
Jinkun Cao, Hao Wu, and Kris Kitani, · 2022
Later among the works it cites.
“Strongsort: Make deepsort great again,”
Yunhao Du, Zhicheng Zhao, Yang Song, Yanyun Zhao, Fei Su, Tao Gong, and Hongying Meng, · 2023
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