Player Identification

Player identification in sports video analysis aims to automatically recognize individual athletes, primarily using jersey numbers, to facilitate various downstream tasks like performance assessment and game analysis. Current research focuses on improving the robustness of identification methods against challenges like motion blur, low resolution, and occlusions, employing architectures such as masked autoencoders, transformers, and convolutional neural networks, often incorporating multi-task learning and keyframe identification techniques. These advancements are crucial for enhancing the efficiency and accuracy of sports analytics, enabling more detailed and insightful studies of athletic performance and team strategies.