DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion

University of Hong Kong · Carnegie Mellon University

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Abstract

A typical pipeline for multi-object tracking (MOT) is to use a detector for object localization, and following re-identification (re-ID)for object association. This pipeline is partially motivated by recent progress in both object detection and re- ID, and partially motivated by biases in existing tracking datasets, where most objects tend to have distin-guishing appearance and re-ID models are sufficient for es-tablishing associations. In response to such bias, we would like to re-emphasize that methods for multi-object tracking should also work when object appearance is not sufficiently discriminative. To this end, we propose a large-scale dataset for multi-human tracking, where humans have sim-ilar…

Citation impact

311
total citations
FWCI
16.82
Percentile
100%
References
64
Citations per year

Authors

7

Topics & keywords

Keywords
  • Computer vision
  • Tracking (education)
  • Computer science
  • Artificial intelligence
  • Motion (physics)
  • Object (grammar)
  • Video tracking
  • Match moving
UN Sustainable Development Goals
  • Reduced inequalities
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