Learning to Estimate 3D Hand Pose from Single RGB Images

Understand

Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images.

• In this paper, we present an approach that estimates 3D hand pose from regular RGB images.
• This task has far more ambiguities due to the missing depth information.
• To this end, we propose a deep network that learns a network-implicit 3D articulation prior.