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Get 3D shape, pose, and relative depth of people from a single image despite occlusion

Get 3D shape, pose, and relative depth of people from a single image despite occlusion


Putting People in their Place: Monocular Regression of 3D People in Depth

arXiv paper abstract https://arxiv.org/abs/2112.08274



Given an image with multiple people, our goal is to directly regress the pose and shape of all the people as well as their relative depth.


... First ... develop a novel method to infer the poses and depth of multiple people in a single image.


... method, called BEV, adds an additional imaginary Bird's-Eye-View representation to explicitly reason about depth.


BEV reasons simultaneously about body centers in the image and in depth and, by combing these, estimates 3D body position.


... exploit a 3D body model space that lets BEV infer shapes from infants to adults.


... BEV outperforms existing methods on depth reasoning, child shape estimation, and robustness to occlusion. ...



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