  Most modern Multi-Object Tracking (MOT) systems typically apply REID-based
paradigm to hold a balance between computational efficiency and performance. In
the past few years, numerous attempts have been made to perfect the systems.
Although they presented favorable performance, they were constrained to track
specified category. Drawing on the ideas of few shot method, we pioneered a new
multi-target tracking system, named MOTS, which is based on metrics but not
limited to track specific category. It contains two stages in series: In the
first stage, we design the self-Adaptive-matching module to perform simple
targets matching, which can complete 88.76% assignments without sacrificing
performance on MOT16 training set. In the second stage, a Fine-match Network
was carefully designed for unmatched targets. With a newly built TRACK-REID
data-set, the Fine-match Network can perform matching of 31 category targets,
even generalizes to unseen categories.
