Training a Feedback Loop for Hand Pose Estimation. - Markus Oberweger; Paul Wohlhart; Vincent Lepetit (ICCV, 2015)

Hands Deep in Deep Learning for Hand Pose Estimation. - Markus Oberweger; Paul Wohlhart; Vincent Lepetit (CoRR, 2015)

Efficiently Creating 3D Training Data for Fine Hand Pose Estimation. - Markus Oberweger; Gernot Riegler; Paul Wohlhart; Vincent Lepetit (CVPR, 2016)

DeepPrior++: Improving Fast and Accurate 3D Hand Pose Estimation. - Markus Oberweger; Vincent Lepetit (ICCV Workshops, 2017)

HandSeg: A Dataset for Hand Segmentation from Depth Images. - Sri Raghu Malireddi; Franziska Mueller 001; Markus Oberweger; Abhishake Kumar Bojja; Vincent Lepetit; Christian Theobalt; Andrea Tagliasacchi (CoRR, 2017)

Domain Transfer for 3D Pose Estimation from Color Images Without Manual Annotations. - Mahdi Rad; Markus Oberweger; Vincent Lepetit (ACCV (5), 2018)

Feature Mapping for Learning Fast and Accurate 3D Pose Inference From Synthetic Images. - Mahdi Rad; Markus Oberweger; Vincent Lepetit (CVPR, 2018)

Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimation. - Markus Oberweger; Mahdi Rad; Vincent Lepetit (ECCV (15), 2018)

Efficient Physics-Based Implementation for Realistic Hand-Object Interaction in Virtual Reality. - Markus Höll; Markus Oberweger; Clemens Arth; Vincent Lepetit (VR, 2018)

HandSeg: An Automatically Labeled Dataset for Hand Segmentation from Depth Images. - Abhishake Kumar Bojja; Franziska Mueller 001; Sri Raghu Malireddi; Markus Oberweger; Vincent Lepetit; Christian Theobalt; Kwang Moo Yi; Andrea Tagliasacchi (CRV, 2019)

HO-3D: A Multi-User, Multi-Object Dataset for Joint 3D Hand-Object Pose Estimation. - Shreyas Hampali; Markus Oberweger; Mahdi Rad; Vincent Lepetit (CoRR, 2019)

HOnnotate: A Method for 3D Annotation of Hand and Object Poses. - Shreyas Hampali; Mahdi Rad; Markus Oberweger; Vincent Lepetit (CVPR, 2020)

Generalized Feedback Loop for Joint Hand-Object Pose Estimation. - Markus Oberweger; Paul Wohlhart; Vincent Lepetit (IEEE Trans. Pattern Anal. Mach. Intell., 2020)