Soccer Video

Research on soccer video analysis focuses on automatically extracting meaningful information from game footage, primarily aiming to improve sports analytics, coaching tools, and fan engagement. Current efforts leverage deep learning, particularly convolutional and recurrent neural networks, and transformer architectures, to perform tasks such as action spotting, player tracking and identification, and even generating real-time commentary or tactical analyses. These advancements are significantly impacting the sports industry by automating previously manual processes, providing more detailed insights into game performance, and enhancing the viewing experience for fans. The development of large, publicly available datasets like SoccerNet has been crucial for driving progress in this field.