Abstract Three-dimensional (3D) human pose estimation involves estimating the articulated
3D joint locations of a human body from an image or video. Due to its widespread …

Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Monocular 3D human pose estimation is quite challenging due to the inherent ambiguity
and occlusion, which often lead to high uncertainty and indeterminacy. On the other hand …

Heatmap-based methods dominate in the field of human pose estimation by modelling the
output distribution through likelihood heatmaps. In contrast, regression-based methods are …

This paper introduces a novel Pre-trained Spatial Temporal Many-to-One (P-STMO) model
for 2D-to-3D human pose estimation task. To reduce the difficulty of capturing spatial and …

Abstract Model-based 3D pose and shape estimation methods reconstruct a full 3D mesh for
the human body by estimating several parameters. However, learning the abstract …

Most of the recent deep learning-based 3D human pose and mesh estimation methods
regress the pose and shape parameters of human mesh models, such as SMPL and MANO …

Abstract In 2D-to-3D pose estimation, it is important to exploit the spatial constraints of 2D
joints, but it is not yet well modeled. To better model the relation of joints for 3D pose …

Estimation of the human pose from a monocular camera has been an emerging research
topic in the computer vision community with many applications. Recently, benefiting from the …

While being the de facto standard coordinate representation for human pose estimation,
heatmap has not been investigated in-depth. This work fills this gap. For the first time, we …