This survey reviews advances in human motion capture and analysis from 2000 to 2006,
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …

Markerless vision-based human motion analysis has the potential to provide an
inexpensive, non-obtrusive solution for the estimation of body poses. The significant …

In this work, we propose a method that combines a single hand-held camera and a set of
Inertial Measurement Units (IMUs) attached at the body limbs to estimate accurate 3D poses …

Direct prediction of 3D body pose and shape remains a challenge even for highly
parameterized deep learning models. Mapping from the 2D image space to the prediction …

Abstract 3D human pose estimation from monocular images is a highly ill-posed problem
due to depth ambiguities and occlusions. Nonetheless, most existing works ignore these …

This paper describes how to obtain accurate 3D body models and texture of arbitrary people
from a single, monocular video in which a person is moving. Based on a parametric body …

We propose a new single-shot method for multi-person 3D pose estimation in general
scenes from a monocular RGB camera. Our approach uses novel occlusion-robust pose …

We introduce HoloPose, a method for holistic monocular 3D human body reconstruction. We
first introduce a part-based model for 3D model parameter regression that allows our …

Human sensing has greatly benefited from recent advances in deep learning, parametric
human modeling, and large scale 2d and 3d datasets. However, existing 3d models make …

Traditionally, monocular 3D human pose estimation employs a machine learning model to
predict the most likely 3D pose for a given input image. However, a single image can be …