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 …

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 …

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 …

To understand how people look, interact, or perform tasks, we need to quickly and
accurately capture their 3D body, face, and hands together from an RGB image. Most …

We present Pose-NDF, a continuous model for plausible human poses based on neural
distance fields (NDFs). Pose or motion priors are important for generating realistic new …

Highlights•Deep neural networks are shattering performance benchmarks in computer
vision for various tasks.•Using modern deep learning approaches (DNNs) in the lab is a …

State-of-the-art human pose estimation methods are based on heat map representation. In
spite of the good performance, the representation has a few issues in nature, such as non …

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 …

Action recognition and human pose estimation are closely related but both problems are
generally handled as distinct tasks in the literature. In this work, we propose a multitask …