1 research outputs found
SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos
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.Comment: This document contains 8 pages + references + supplementary materia