Human pose estimation using deep neural networks aims to map input images with large
variations into multiple body keypoints, which must satisfy a set of geometric constraints and …

Currently, Computer Vision (CV) is one of the most popular research topics in the world. This
is because it can support the human daily life. Moreover, CV can also apply to various …

This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in
2011 (with the release of the first Kinect device) to run challenges related to human …

The recovery of 3D human pose with monocular camera is an inherently ill-posed problem
due to the large number of possible projections from the same 2D image to 3D space. Aimed …

Numerical weather forecasting on high-resolution physical models consume hours of
computations on supercomputers. Application of deep learning and machine learning …

Virtual training has received a considerable amount of research attention in recent years
due to its potential for use in a variety of applications, such as virtual military training, virtual …

The neural network based approach for 3D human pose estimation from monocular images
has attracted growing interest. However, annotating 3D poses is a labor-intensive and …

3D human pose estimation describes estimating 3D articulation structure of a person from
an image or a video. The technology has massive potential because it can enable tracking …

Both accuracy and efficiency are of equal importance to the human pose estimation. Most of
the existing methods simply pursue excellent performance, sacrificing massive computing …

This paper explores the capabilities of convolutional neural networks to deal with a task that
is easily manageable for humans: perceiving 3D pose of a human body from varying angles …