Global 3D Human Pose Estimation

Global 3D Human Pose Estimation is a significant task in the field of computer vision, aiming to recover the precise positions of human joints in the world coordinate system from monocular images, rather than relative to the camera coordinates. This task enhances the accuracy and robustness of pose estimation by capturing errors in the global coordinate system, which is crucial for applications such as virtual reality, motion capture, and human-computer interaction. GLAMR (Yuan et al., CVPR 2022) was the first to introduce this method under a monocular setting.