BlazePose-MSF: An Optimized Real-Time Human Pose Estimation Method Based on Multi-Scale Fusion

In this paper, we propose a real-time human pose estimation optimization method called BlazePose-MSF, which is based on multi-scale feature fusion technique and achieves low latency while maintaining high accuracy. By introducing a lightweight network architecture and a channel compression strategy, the computational complexity and the number of model parameters are significantly reduced, making it suitable for resource-constrained mobile devices. Experiments show that BlazePose-MSF strikes a better balance between accuracy and efficiency than existing methods.