Hand pose estimation through semi-supervised and weakly-supervised learning.

•Handpose estimation with direct regression from depth plus segmentation maps.•We exploit strong topological and structural information in segmentation maps.•An offline restoration process creates loss for unlabeled data.•This intermediate representation allows adaptation from synthetic to real data.