The Application of Adaptive Residual Module Optimisation Transformer Model in Sports Training Human Pose Estimation

Key Points

• To explore the effectiveness of a transformer model in estimating human pose during sports training.
• Developed an adaptive residual module within a transformer framework.
• Implemented the model in the context of sports training scenarios.
• Evaluated the model's performance in estimating human poses accurately.
• Achieved higher accuracy in human pose estimation compared to traditional methods.
• Demonstrated improved training outcomes through optimized pose tracking in athletes.
• Revealed that this approach can adapt to various sports scenarios effectively.