Research on Human Pose Estimation Model Based on Long-Range Fine-Grained Modeling

human pose estimation Yolopose coordinate attention spatial pyramid pooling implicit knowledge

Authors

  • Ziyang Lin School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China,454003
  • Bo Su School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, China,454003
April 23, 2024
April 25, 2024

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To address the issues of lacking long-range spatial position learning ability and excessive loss of fine-grained feature information during spatial feature pooling in human pose estimation models, a novel human pose estimation model based on the Yolopose network is proposed. Firstly, an enhanced coordinate attention module is introduced and embedded into the backbone network to endow the model with long-range spatial position modeling capability. Secondly, a fine-grained cascaded spatial pyramid pooling module is proposed to mitigate the loss of fine-grained feature information caused by spatial feature pooling. Finally, an implicit knowledge learning module is incorporated to reduce the model parameter count and enhance the model's capability for multi-task joint optimization.