3D reconstruction is a longstanding ill-posed problem, which has been explored for decades
by the computer vision, computer graphics, and machine learning communities. Since 2015 …

This work addresses the problem of estimating the full body 3D human pose and shape from
a single color image. This is a task where iterative optimization-based solutions have …

Human shape estimation is an important task for video editing, animation and fashion
industry. Predicting 3D human body shape from natural images, however, is highly …

We present DenseRaC, a novel end-to-end framework for jointly estimating 3D human pose
and body shape from a monocular RGB image. Our two-step framework takes the body pixel …

We introduce a new silhouette-based representation for modeling clothed human bodies
using deep generative models. Our method can reconstruct a complete and textured 3D …

We present Octopus, a learning-based model to infer the personalized 3D shape of people
from a few frames (1-8) of a monocular video in which the person is moving with a …

Parametric modeling of 3D body shape is widely used to create realistic human bodies. It
furthermore permits robust reconstruction of complete 3D body shapes even from …

This paper presents a novel framework to recover detailed human body shapes from a
single image. It is a challenging task due to factors such as variations in human shapes …

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 …

We propose a scalable neural network framework to reconstruct the 3D mesh of a human
body from multi-view images, in the subspace of the SMPL model. Use of multi-view images …