No Train Yet Gain: Towards Generic Multi-Object Tracking in Sports and Beyond
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Abstract (arXiv)
Multi-object tracking (MOT) is essential for sports analytics, enabling performance evaluation and tactical insights. However, tracking in sports is challenging due to fast movements, occlusions, and camera shifts. Traditional tracking-by-detection methods require extensive tuning, while segmentation-based approaches struggle with track processing. We propose McByte, a tracking-by-detection framework that integrates temporally propagated segmentation mask as an association cue to improve robustness without per-video tuning. Unlike many existing methods, McByte does not require training, relying solely on pre-trained models and object detectors commonly used in the community. Evaluated on SportsMOT, DanceTrack, SoccerNet-tracking 2022 and MOT17, McByte demonstrates strong performance across sports and general pedestrian tracking. Our results highlight the benefits of mask propagation for a more adaptable and generalizable MOT approach. Code will be made available at https://github.com/tstanczyk95/McByte.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 37 of its 46 references that are in the map. First posted on arXiv 2 Jun 2025.
Builds on
37 of 46 references.
References · 37
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2014Microsoft COCO: Common Objects in Contextcited by 17,608
- 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,139
- 2023Segment Anythingcited by 8,234
- 2019Parameter-Efficient Transfer Learning for NLPcited by 4,236
- 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,332
- 2024SAM 2: Segment Anything in Images and Videoscited by 2,863
- 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,071
- 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 823
- 2016Performance Measures and a Data Set for Multi-Target, Multi-Camera Trackingcited by 692
- 2022Detecting Twenty-thousand Classes using Image-level Supervisioncited by 614
- 2020HOTA: A Higher Order Metric for Evaluating Multi-Object Trackingcited by 552
25 more
- 2016MOT16: A Benchmark for Multi-Object Trackingcited by 532
- 2020FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Trackingcited by 490
- 2020Tracking Objects as Pointscited by 483
- 2022XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Modelcited by 439
- 2021MOTR: End-to-End Multiple-Object Tracking with Transformercited by 381
- 2022Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Trackingcited by 346
- 2021DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motioncited by 217
- 2023Tracking Anything with Decoupled Video Segmentationcited by 197
- 2023Putting the Object Back into Video Object Segmentationcited by 188
- 2022MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectorscited by 148
- 2020MOTChallenge: A Benchmark for Single-Camera Multiple Target Trackingcited by 136
- 2023Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identificationcited by 132
- 2023SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenescited by 131
- 2023MeMOTR: Long-Term Memory-Augmented Transformer for Multi-Object Trackingcited by 88
- 2022SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videoscited by 80
- 2023Hybrid-SORT: Weak Cues Matter for Online Multi-Object Trackingcited by 67
- 2022Hard to Track Objects with Irregular Motions and Similar Appearances? Make It Easier by Buffering the Matching Spacecited by 66
- 2022Unifying Short and Long-Term Tracking with Graph Hierarchiescited by 62
- 2024Multiple Object Tracking as ID Predictioncited by 60
- 2024DiffMOT: A Real-time Diffusion-based Multiple Object Tracker with Non-linear Predictioncited by 59
- 2021RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representationcited by 52
- 2024Matching Anything by Segmenting Anythingcited by 50
- 2022GIAOTracker: A comprehensive framework for MCMOT with global information and optimizing strategies in VisDrone 2021cited by 46
- 2024Towards Generalizable Multi-Object Trackingcited by 23
- 2022The Second-place Solution for CVPR 2022 SoccerNet Tracking Challengecited by 2
Built on by
Citing papers per year: 2025: 2; 2026: 4.
6 papers.
- 2025Look Around and Pay Attention: Multi-camera Point Tracking Reimagined with Transformerscited by 4
- 2025Multi Camera Connected Vision System with Multi View Analytics: A Comprehensive Surveycited by 1
- 2026SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarioscited by 1
- 2026WaspMOT: A Benchmark for Long-Term Multi-Object Tracking of Trichogramma Waspscited by 0
- 2026Training-Free Long-Term Multi-Object Tracking for Sports Video Analyticscited by 0
- 2026Revisiting Multi-Object Tracking Baselines: Hyperparameter Optimization with Multi-Fidelity Greedy Coordinate Searchcited by 0
- 2026Revisiting Multi-Object Tracking Baselines: Hyperparameter Optimization with Multi-Fidelity Greedy Coordinate Search10 Sep 2026
- 2026Training-Free Long-Term Multi-Object Tracking for Sports Video Analytics16 Aug 2026
- 2026WaspMOT: A Benchmark for Long-Term Multi-Object Tracking of Trichogramma Wasps9 Jul 2026
- 2026SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios24 Apr 2026
- 2025Look Around and Pay Attention: Multi-camera Point Tracking Reimagined with Transformers3 Dec 2025
- 2025Multi Camera Connected Vision System with Multi View Analytics: A Comprehensive Survey10 Oct 2025