SoccerNet 2023 Tracking Challenge -- 3rd place MOT4MOT Team Technical
  Report
Gal Shitrit Ishay Be'ery Ido Yerhushalmy
The SoccerNet 2023 tracking challenge requires the detection and tracking of
soccer players and the ball. In this work, we present our approach to tackle
these tasks separately. We employ a state-of-the-art online multi-object
tracker and a contemporary object detector for player tracking. To overcome the
limitations of our online approach, we incorporate a post-processing stage
using interpolation and appearance-free track merging. Additionally, an
appearance-based track merging technique is used to handle the termination and
creation of tracks far from the image boundaries. Ball tracking is formulated
as single object detection, and a fine-tuned YOLOv8l detector with proprietary
filtering improves the detection precision. Our method achieves 3rd place on
the SoccerNet 2023 tracking challenge with a HOTA score of 66.27.