RTMPose introduces a real-time, top-down human pose estimation framework that jointly optimizes model architecture and training strategy to achieve high accuracy under strict latency constraints.

Original paper: RTMPose: Real-Time Multi-Person Pose Estimation Based on MMPose

This model uses the RTMPose-M variant, which strikes a balance between accuracy and inference speed through efficient backbone design and optimized keypoint heads. It is well suited for real-time pose estimation in applications such as human–computer interaction, sports analytics, video surveillance, and edge AI systems.

Model Configuration: