How To Train Your Deep Multi-Object Tracker

15 Jun 2019Yihong XuAljosa OsepYutong BanRadu HoraudLaura Leal-TaixeXavier Alameda-Pineda

The recent trend in vision-based multi-object tracking (MOT) is heading towards leveraging the representational power of deep learning to jointly learn to detect and track objects. However, existing methods train only certain sub-modules using loss functions that often do not correlate with established tracking evaluation measures such as Multi-Object Tracking Accuracy (MOTA) and Precision (MOTP)... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Multi-Object Tracking 2D MOT 2015 DeepMOT-Tracktor MOTA 44.1 # 1
Multi-Object Tracking MOT16 DeepMOT-Tracktor MOTA 54.8 # 3
Multi-Object Tracking MOT17 DeepMOT-Tracktor MOTA 53.7 # 2