Convolutional Mesh Regression for Single-Image Human Shape Reconstruction

Understand

This paper addresses the problem of 3D human pose and shape estimation from a single image.

• Previous approaches consider a parametric model of the human body, SMPL, and attempt to regress the model parameters that give rise to a mesh consistent with image evidence.
• This parameter regression has been a very challenging task, with model-based approaches underperforming compared to nonparametric solutions in terms of pose estimation.
• In our work, we propose to relax this heavy reliance on the model's parameter space.