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Article summary:
1. A new multi-object tracking (MOT) method, ByteTrack, is proposed which associates almost every detection box instead of only the high score ones.
2. ByteTrack achieves state-of-the-art performance on MOT17, MOT20, HiEve and BDD100K tracking benchmarks.
3. The source code, pre-trained models with deploy versions and tutorials of applying to other trackers are released online.
Article analysis:
The article is generally reliable and trustworthy in its reporting of the proposed ByteTrack method for multi-object tracking (MOT). The authors provide a detailed description of the method and its results on various benchmark datasets, as well as a link to the source code and pre-trained models for further exploration by readers. The article does not appear to be biased or one-sided in its reporting; it presents both sides equally by providing an overview of existing methods as well as a detailed description of the proposed ByteTrack method. Furthermore, the authors provide evidence for their claims in the form of quantitative results from experiments conducted on various benchmark datasets.
The article does not appear to have any missing points of consideration or missing evidence for its claims; all relevant information is provided in detail. Additionally, there are no unexplored counterarguments or promotional content present in the article; it is focused solely on presenting the proposed ByteTrack method and its results objectively without any bias or promotion. Finally, possible risks associated with using this method are noted in the discussion section at the end of the paper. In conclusion, this article appears to be reliable and trustworthy overall.