  We introduce a technique for 3D human keypoint estimation that directly
models the notion of spatial uncertainty of a keypoint. Our technique employs a
principled approach to modelling spatial uncertainty inspired from techniques
in robust statistics. Furthermore, our pipeline requires no 3D ground truth
labels, relying instead on (possibly noisy) 2D image-level keypoints. Our
method achieves near state-of-the-art performance on Human3.6m while being
efficient to evaluate and straightforward to
