Sport Scene

Research on sports scenes focuses on leveraging computer vision and machine learning to analyze video footage for enhanced understanding and application in sports analytics and broadcasting. Current efforts concentrate on developing robust models for tasks such as human-human interaction detection, instance segmentation of players, and accurate multi-object tracking, often employing deep neural networks and novel architectures like neural radiance fields (NeRFs) for novel view synthesis. These advancements enable more precise performance evaluation, automated tactical analysis, and improved visualization tools for coaches and analysts, ultimately contributing to data-driven decision-making in various sports.