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 …

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 …

Human pose estimation (HPE) has developed over the past decade into a vibrant field for
research with a variety of real-world applications like 3D reconstruction, virtual testing and re …

Human pose estimation from single images is a challenging problem that is typically solved
by supervised learning. Unfortunately, labeled training data does not yet exist for many …

This paper addresses the problem of cross-dataset generalization of 3D human pose
estimation models. Testing a pre-trained 3D pose estimator on a new dataset results in a …

Monocular 3D human pose estimation technologies have the potential to greatly increase
the availability of human movement data. The best-performing models for single-image 2D …

Abstract 3D human pose estimation is fundamental to understanding human behavior.
Recently, promising results have been achieved by graph convolutional networks (GCNs) …

Due to the lack of diversity of datasets, the generalization ability of the pose estimator is
poor. To solve this problem, we propose a pose augmentation solution via DH forward …

The 2D-3D lifting task for Human Pose Estimation is a highly nonlinear mapping problem,
which requires mutual constraints among human joints. In this paper, we mainly discuss how …

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 …