This work presents improvements in monocular hand shape estimation by building on top of recent advances in unsupervised learning.
We show that methods trained on our dataset consistently perform well when tested on other datasets.
Ranked #8 on 3D Hand Pose Estimation on FreiHAND
We propose an approach to estimate 3D human pose in real world units from a single RGBD image and show that it exceeds performance of monocular 3D pose estimation approaches from color as well as pose estimation exclusively from depth.
Ranked #14 on 3D Human Pose Estimation on Total Capture
Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images.