the problem of tracking people, which is particularly interesting both for real-world applications, as well as for downstream tasks, like action detection in videos [@zhang2019structured; @li2018recurrent; @gao2018ctap; @choi2012unified]. Our Siamese Track-RCNN achieves state-of-the-art (SOTA) performance on both MOT16 (59.8 MOTA) and MOT17 (59.6 MOTA) of the MOTChallenge. Finally, we present an extensive ablation study of Siamese Track-RCNN on a large-scale synthetic dataset: Joint Track Auto (JTA) [@fabbri2018learning]. We show that our model can accurately localize person instances in crowded scenes and consistently track them over long periods of time.

Related work
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Multi-object tracking (MOT)
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Most works on MOT adopt the “tracking-by-detection" framework paradigm  [@zhang2008global; @berclaz2011multiple; @zamir2012gmcp; @kim2015multiple; @tang2017multiple; @henschel2017improvements; @ristani2018features; @keuper2018motion; @sheng2018heterogeneous; @xu2019spatial; @xu2019train; @sadeghian2017tracking; @leal2016learning; @wang2019exploit; @andriyenko2011multi; @berclaz2006robust; @choi2010multiple; @evangelidis2008parametric; @fang2018recurrent], in which detected object instances are associated across time based on their visual coherence and spatial-temporal consistency. Some of these works focused on learning new functions to evaluate short-term associations more robustly [@ristani2018features; @sheng2018heterogeneous; @tang2017multiple; @xu2019spatial; @zhang2008global; @tang2017multiple; @sadeghian2017tracking; @leal2016learning; @choi2015near; @fang2018recurrent; @zhang2008global]. Others, instead, focused on learning how to output more temporally consistent long-term tracks by optimizing locally connected graphs [@zhang2008global; @berclaz2011multiple; @zamir2012gmcp; @kim2015multiple; @tang2017multiple; @henschel2017improvements; @ristani2018features; @keuper2018motion; @sheng2018heterogeneous; @xu2019spatial; @xu2019train; @wang2019exploit; @andriyenko2011multi; @berclaz2006robust; @evangelidis2008parametric; 