: 500 complete soccer games from major European leagues (2014–2017), totaling 764 hours of video.
Since the original v1 release, the dataset has expanded significantly into newer versions: SoccerStar-v1-pc_UQ.7z
A Scalable Dataset for Action Spotting in Soccer Videos - arXiv : 500 complete soccer games from major European
: The paper proposes using recent developments in action recognition and detection to provide baselines, reaching a mean Average Precision (mAP) of 67.8% for classifying 1-minute temporal segments. Evolutions of the Dataset : Focuses on three
: It addressed the lack of large-scale, publicly available datasets for automated soccer video understanding, enabling the training of deep learning models for sports analytics. Evolutions of the Dataset
: Focuses on three primary event types: Goals , Yellow/Red Cards , and Substitutions .
The file likely contains the first version of the SoccerNet dataset (often referred to as SN-v1 ), which is the foundation for the landmark paper SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos . The "Deep" Paper: SoccerNet (SN-v1)