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The SportsMOT dataset aims to solve multiple object tracking of athletes indifferent sports scenes such as basketball or soccer. The dataset ischallenging because of the unstable camera view, athletes' complex trajectory,and complicated background. Previous MOT methods can not match enoughhigh-quality tracks of athletes. To pursue higher performance of MOT in sportsscenes, we introduce an innovative tracker named SportsTrack, we utilizetracking by detection as our detection paradigm. Then we will introduce athree-stage matching process to solve the motion blur and body overlapping insports scenes. Meanwhile, we present another innovation point: one-to-manycorrespondence between detection bboxes and crowded tracks to handle theoverlap of athletes' bodies during sports competitions. Compared to othertrackers such as BOT-SORT and ByteTrack, We carefully restored edge-lost tracksthat were ignored by other trackers. Finally, we reached the SOTA result in theSportsMOT dataset.

SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes