  This is a brief technical report of our proposed method for Multiple-Object
Tracking (MOT) Challenge in Complex Environments. In this paper, we treat the
MOT task as a two-stage task including human detection and trajectory matching.
Specifically, we designed an improved human detector and associated most of
detection to guarantee the integrity of the motion trajectory. We also propose
a location-wise matching matrix to obtain more accurate trace matching. Without
any model merging, our method achieves 66.672 HOTA and 93.971 MOTA on the
DanceTrack challenge dataset.
