Multi-person pose estimation is a fundamental issue in sports analysis, which entails tracking the movements of numerous players concurrently. Precisely detecting and tracing the body postures of players can furnish valuable insights into their performance, enabling coaches and analysts to make well-informed decisions. However, existing pose estimation methodologies often encounter difficulties in dealing with the intricate and rapidly evolving situations that are typical in sports, leading to imprecise or partial pose estimations. Thus, there is an exigency for a resilient and real-time multi-person pose estimation system custom-built for sports analysis, proficient in managing swift motions and occlusions while maintaining optimal accuracy.
