Fast and Accurate 3D hand-object Pose Estimation for Embedded Applications

Understanding human activities in everyday and professional scenarios requires fast and accurate 3D hand-object pose estimation. Most existing 3D hand-object pose estimation models rely on dedicated hardware support to address these challenges, limiting their practicality on everyday devices such as smartphones. In this paper, we propose a lightweight solution for hand and object pose estimation for mobile applications, using only RGB images as input, which greatly improves efficiency while maintaining high accuracy, demonstrating the feasibility of real-time hand pose estimation in low-computation environments. This makes a new contribution to interactive applications centered on the human hand under hardware constraints.