Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer

What is it about?

In this survey, we explore how modern computer vision and machine learning techniques are transforming the way soccer actions and events are automatically understood from video. With the rapid growth of sports analytics, automated detection of passes, shots, tackles, goals, and complex spatio-temporal interactions has become a key research challenge. Our paper reviews the state of the art in three major tasks: - action recognition: identifying what players are doing within short video clips, - action spotting: automatically determining when key events occur in long, untrimmed broadcasts, - spatio-temporal localization: detecting what happens, where it happens, and when it occurs on the field. We highlight the latest models, benchmark datasets, and evaluation metrics, and discuss how current approaches are shaping the next steps in soccer video understanding.

Featured Image

Photo by Vikram TKV on Unsplash

Photo by Vikram TKV on Unsplash

Why is it important?

Accurate and scalable soccer analysis has huge potential for: - professional coaching and tactical evaluation, - automatic event detection for broadcasters, - performance scouting and player profiling, - enhanced fan engagement and match insights.