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 …

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 …

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 …

In this paper, we propose a novel graph convolutional network architecture, Graph Stacked
Hourglass Networks, for 2D-to-3D human pose estimation tasks. The proposed architecture …

Human pose estimation has received significant attention recently due to its various
applications in the real world. As the performance of the state-of-the-art human pose …

We propose a method for human pose estimation based on Deep Neural Networks (DNNs).
The pose estimation is formulated as a DNN-based regression problem towards body joints …

Human pose estimation has made significant progress during the last years. However
current datasets are limited in their coverage of the overall pose estimation challenges. Still …

Recently dense trajectories were shown to be an efficient video representation for action
recognition and achieved state-of-the-art results on a variety of datasets. This paper …

In recent years, there has been a proliferation of works on human action classification from
depth sequences. These works generally present methods and/or feature representations …

We propose a ConvNet model for predicting 2D human body poses in an image. The model
regresses a heatmap representation for each body keypoint, and is able to learn and …