A structured latent space for human body motion generation. (arXiv:2106.04387v4 [cs.CV] UPDATED)

We propose a framework to learn a structured latent space to represent 4D
human body motion, where each latent vector encodes a full motion of the whole
3D human shape. On one hand several data-driven skeletal animation models exist
proposing motion spaces of temporally dense motion signals, but based on
geometrically sparse kinematic representations. On the other hand many methods
exist to build shape spaces of dense 3D geometry, but for static frames. We
bring together both concepts, proposing a …

arxiv generation human space