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 …

Abstract We describe Human Mesh Recovery (HMR), an end-to-end framework for
reconstructing a full 3D mesh of a human body from a single RGB image. In contrast to most …

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

We present the first real-time method to capture the full global 3D skeletal pose of a human
in a stable, temporally consistent manner using a single RGB camera. Our method combines …

We describe the first method to automatically estimate the 3D pose of the human body as
well as its 3D shape from a single unconstrained image. We estimate a full 3D mesh and …

We propose a CNN-based approach for 3D human body pose estimation from single RGB
images that addresses the issue of limited generalizability of models trained solely on the …

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 …

Our ability to train end-to-end systems for 3D human pose estimation from single images is
currently constrained by the limited availability of 3D annotations for natural images. Most …

Automatic emotion recognition has become a trending research topic in the past decade.
While works based on facial expressions or speech abound, recognizing affect from body …