Challenges in 3D human pose estimation include occlusions (body parts being hidden), self-occlusions (body parts blocking each other), varying camera viewpoints, and the ambiguity inherent in 2D-to-3D mapping. Researchers and engineers have developed various techniques to address these challenges, such as data augmentation, multi-modal fusion, and using additional cues like clothing information.We propose a novel monocular 3D human pose refining method combining accurate bone length constraints and artificial localization errors.
MoveNet