Papers › MotionTrack: Learning Motion Predictor for Multiple Object Tracking
MotionTrack: Learning Motion Predictor for Multiple Object Tracking
Changcheng Xiao, Qiong Cao, Yujie Zhong, Long Lan, Xiang Zhang, Zhigang Luo, DaCheng Tao
Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accurately tracking objects in scenarios with homogeneous appearance and heterogeneous motion remains a challenge. This challenge arises from two main factors: the insufficient discriminability of ReID features and the predominant utilization of linear motion models in MOT. In this context, we introduce a novel motion-based tracker, MotionTrack, centered around a learnable motion predictor that relies solely on object trajectory information. This predictor comprehensively integrates two levels of granularity in motion features to enhance the modeling of temporal dynamics and facilitate precise future motion prediction for individual objects. Specifically, the proposed approach adopts a self-attention mechanism to capture token-level information and a Dynamic MLP layer to model channel-level features. MotionTrack is a simple, online tracking approach. Our experimental results demonstrate that MotionTrack yields state-of-the-art performance on datasets such as Dancetrack and SportsMOT, characterized by highly complex object motion.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multi-Object Tracking | DanceTrack | MotionTrack | AssA | 41.7 | #23 of 37 | Archive leaderboard | report |
| Multi-Object Tracking | DanceTrack | MotionTrack | DetA | 81.4 | #23 of 37 | Archive leaderboard | report |
| Multi-Object Tracking | DanceTrack | MotionTrack | HOTA | 58.2 | #23 of 37 | Archive leaderboard | report |
| Multi-Object Tracking | DanceTrack | MotionTrack | IDF1 | 58.6 | #23 of 37 | Archive leaderboard | report |
| Multi-Object Tracking | DanceTrack | MotionTrack | MOTA | 91.3 | #23 of 37 | Archive leaderboard | report |
| Multi-Object Tracking | SportsMOT | MotionTrack | AssA | 61.7 | #11 of 22 | Archive leaderboard | report |
| Multi-Object Tracking | SportsMOT | MotionTrack | DetA | 88.8 | #11 of 22 | Archive leaderboard | report |
| Multi-Object Tracking | SportsMOT | MotionTrack | HOTA | 74.0 | #11 of 22 | Archive leaderboard | report |
| Multi-Object Tracking | SportsMOT | MotionTrack | IDF1 | 74.0 | #11 of 22 | Archive leaderboard | report |
| Multi-Object Tracking | SportsMOT | MotionTrack | MOTA | 96.6 | #11 of 22 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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