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 …

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 …

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 …

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 …

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 …

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 …

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 …

In this work, we demonstrate that 3D poses in video can be effectively estimated with a fully
convolutional model based on dilated temporal convolutions over 2D keypoints. We also …

Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …

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 …