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The SoccerNet 2023 tracking challenge requires the detection and tracking ofsoccer players and the ball. In this work, we present our approach to tacklethese tasks separately. We employ a state-of-the-art online multi-objecttracker and a contemporary object detector for player tracking. To overcome thelimitations of our online approach, we incorporate a post-processing stageusing interpolation and appearance-free track merging. Additionally, anappearance-based track merging technique is used to handle the termination andcreation of tracks far from the image boundaries. Ball tracking is formulatedas single object detection, and a fine-tuned YOLOv8l detector with proprietaryfiltering improves the detection precision. Our method achieves 3rd place onthe SoccerNet 2023 tracking challenge with a HOTA score of 66.27.

SoccerNet 2023 Tracking Challenge -- 3rd place MOT4MOT Team Technical Report