no code implementations • 8 Jun 2021 • Christian Zimmermann, Max Argus, Thomas Brox
This work presents improvements in monocular hand shape estimation by building on top of recent advances in unsupervised learning.
no code implementations • ICCV 2019 • Christian Zimmermann, Duygu Ceylan, Jimei Yang, Bryan Russell, Max Argus, Thomas Brox
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
1 code implementation • 7 Mar 2018 • Christian Zimmermann, Tim Welschehold, Christian Dornhege, Wolfram Burgard, Thomas Brox
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
8 code implementations • ICCV 2017 • Christian Zimmermann, Thomas Brox
Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images.