The human pose estimation is a significant issue that has been taken into consideration in
the computer vision network for recent decades. It is a vital advance toward understanding …

Estimating the pose of a human in 3D given an image or a video has recently received
significant attention from the scientific community. The main reasons for this trend are the …

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 …

Following the success of deep convolutional networks, state-of-the-art methods for 3d
human pose estimation have focused on deep end-to-end systems that predict 3d joint …

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 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 addresses the challenge of 3D human pose estimation from a single color image.
Despite the general success of the end-to-end learning paradigm, top performing …

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 …

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 …