Papers › Spiideo SoccerNet SynLoc: Single Frame World Coordinate Athlete Detection and...

Spiideo SoccerNet SynLoc: Single Frame World Coordinate Athlete Detection and Localization with Synthetic Data

27 Feb 2025VISAPP 2025 2archive 2025-07-28

Håkan Ardö, Mikael Nilsson, Anthony Cioppa, Floriane Magera, Silvio Giancola, Haochen Liu, Bernard Ghanem, Marc Van Droogenbroeck

Currently, most research and public datasets for video sports analytics are base on detecting players as bounding boxes in broadcast videos. Going from there to precise locations on the pitch is however hard. Modern solutions are making dedicated static cameras covering the entire pitch more readily accessible, and they are now used more and more even in lower tiers. To promote research that can take benefits of such cameras and produce more precise pitch locations, we introduce the Spiideo SoccerNet SynLoc dataset. It consists of synthetic athletes rendered on top of images from real world installation of such cameras. We also introduce a new task of detecting the players in the world pitch coordinate system and a new metric based solely on real world physical properties where the representation in the image is irrelevant. The dataset and code are publicly available at https://github. com/Spiideo/sskit.

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Code

spiideo/sskit officialmentioned in paperpytorch report
Spiideo/mmpose mentioned in paperpytorch report

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Tasks

3D Object DetectionSports Analytics

Datasets

Introduced by this paper, per the archive.

Spiideo SoccerNet SynLoc

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
3D Object Detection Spiideo SoccerNet SynLoc Baseline-960x960 F1 89.0 #1 of 2 Archive leaderboard report
3D Object Detection Spiideo SoccerNet SynLoc Baseline-960x960 FrameAccuracy 31.6 #1 of 2 Archive leaderboard report
3D Object Detection Spiideo SoccerNet SynLoc Baseline-960x960 mAP-LocSim 79.3 #1 of 2 Archive leaderboard report
3D Object Detection Spiideo SoccerNet SynLoc Baseline-640x640 F1 83.6 #2 of 2 Archive leaderboard report
3D Object Detection Spiideo SoccerNet SynLoc Baseline-640x640 FrameAccuracy 15.4 #2 of 2 Archive leaderboard report
3D Object Detection Spiideo SoccerNet SynLoc Baseline-640x640 mAP-LocSim 67.8 #2 of 2 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

BASE

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