SMOT: Single-Shot Multi Object Tracking
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Abstract (arXiv)
We present single-shot multi-object tracker (SMOT), a new tracking framework that converts any single-shot detector (SSD) model into an online multiple object tracker, which emphasizes simultaneously detecting and tracking of the object paths. Contrary to the existing tracking by detection approaches which suffer from errors made by the object detectors, SMOT adopts the recently proposed scheme of tracking by re-detection. We combine this scheme with SSD detectors by proposing a novel tracking anchor assignment module. With this design SMOT is able to generate tracklets with a constant per-frame runtime. A light-weighted linkage algorithm is then used for online tracklet linking. On three benchmarks of object tracking: Hannah, Music Videos, and MOT17, the proposed SMOT achieves state-of-the-art performance.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Oct 2020.
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Citing papers per year: 2021: 1; 2022: 1.
2 papers.
- 2022Recent Advances in Embedding Methods for Multi-Object Tracking: A Surveycited by 8
- 2021Localization-Based Trackingcited by 0
- 2022Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey22 May 2022
- 2021Localization-Based Tracking12 Apr 2021