Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images

Understand

In this paper, we tackle the problem of 3D human shape estimation from single RGB images.

• While the recent progress in convolutional neural networks has allowed impressive results for 3D human pose estimation, estimating the full 3D shape of a person is still an open issue.
• Model-based approaches can output precise meshes of naked under-cloth human bodies but fail to estimate details and un-modelled elements such as hair or clothing.
• On the other hand, non-parametric volumetric approaches can potentially estimate complete shapes but, in practice, they are limited by the resolution of the output grid and cannot produce detailed estimates.