GLAMR (Left) recovers human meshes in consistent global coordinates from videos captured by dynamic cameras and infills missing poses (transparent) due to various
occlusions (obstruction, missed detection, outside field of view), while standard human mesh recovery methods (Right) fail to do so.
Abstract
We present an approach for 3D global human mesh recovery from monocular videos recorded with dynamic cameras. Our approach is robust to severe and long-term occlusions and tracks human bodies even when they go outside the camera’s field of view. To achieve this, we first propose a deep generative motion infiller, which autoregressively infills the body motions of occluded humans based on visible motions. Additionally, in contrast to prior work, our approach reconstructs human meshes in consistent global coordinat
