Referee detection: Datasets & Models
Referee detection locates and tracks match officials in sports footage, distinguishing them from players so analytics pipelines don't confuse referees with athletes.
Referee detection
This detection workflow locates referees in sports footage and draws bounding boxes around match officials, keeping them separate from players, coaches, and spectators. It accepts images or video frames from broadcasts, stadium cameras, or training clips, and you can train it on a referee dataset to fit your specific sport and camera angles.
Try it out
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Why automate referee detection
In sports analytics, manually annotating every frame to flag which figure is a referee is slow, tedious, and impractical at broadcast scale. Automating referee detection lets teams cleanly exclude officials from player tracking, heat maps, and possession statistics without human review. It also enables use cases like evaluating referee positioning relative to play or triggering camera cuts. The result is cleaner data and less manual cleanup for analysts and production crews.
Key benefits
Automated referee detection removes officials as noise from player-tracking pipelines, improving the accuracy of downstream analytics. It runs on the camera feeds and archived footage sports organizations already have, and scales from a single match to full-season libraries. Training on a dedicated referee dataset with RF-DETR delivers reliable detection even in crowded, fast-moving scenes.
How to use it
- Upload an image: Drop any photo into the widget above to try referee detection for free, right on this page.
- Preview instant results: The model detects referee, player, goalkeeper, soccer ball, coach within seconds and returns an annotated image with structured predictions, so you can immediately see how well it works. Adjust the detection classes and re-run until the results fit your scenario.
- Like what you see?: With a free Roboflow account, you can deploy this workflow with the Serverless Cloud API, customize it in your workspace, or train RF-DETR on your own images for production accuracy.
- Get started for free: No code or training data required to begin: upload, review the results, and make it part of your stack in a single click.
Recommended model for referee detection
RF-DETR is state of the art for real-time object detection, instance segmentation, and keypoint detection, with higher accuracy and lower latency than comparable models, and it's Apache 2.0 licensed. When you're ready to build a production model for referee detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Referee Detection project to Roboflow Agent.