2020/11/26 by Adrien Deliège, Deliège, Adrien, Anthony Cioppa +16 · 25 citations
Computer Science · Economics, Econometrics and Finance · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Sports Analytics and Performance #Video Analysis and Summarization #cs.CV
paper · pdf · doi:10.48550/arxiv.2011.13367
Paper accepted for the CVsports workshop at CVPR2021. This document contains 8 pages + references + supplementary material
openalex publication_date 2020/11/26 · arxiv created 2021/04/19 · arxiv updated 2021/04/20 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Understanding broadcast videos is a challenging task in computer vision, as it requires generic reasoning capabilities to appreciate the content offered by the video editing. In this work, we propose SoccerNet-v2, a novel large-scale corpus of manual annotations for the SoccerNet video dataset, along with open challenges to encourage more research in soccer understanding and broadcast production. Specifically, we release around 300k annotations within SoccerNet's 500 untrimmed broadcast soccer videos. We extend current tasks in the realm of soccer to include action spotting, camera shot segmentation with boundary detection, and we define a novel replay grounding task. For each task, we provide and discuss benchmark results, reproducible with our open-source adapted implementations of the most relevant works in the field. SoccerNet-v2 is presented to the broader research community to help push computer vision closer to automatic solutions for more general video understanding and production purposes.