At a time when adult education is being digitized at breakneck speed, a counter-trend is asserting itself: that of a return to the body, to materiality and to objects as living supports for learning.

Estimating the pose of hand-held objects is a critical and challenging problem in robotics and computer vision. While leveraging multi-modal RGB and depth data is a promising solution, existing ...