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 …

Human motion generation aims to generate natural human pose sequences and shows
immense potential for real-world applications. Substantial progress has been made recently …

Inspired by the success of volumetric 3D pose estimation, some recent human mesh
estimators propose to estimate 3D skeletons as intermediate representations, from which …

Egocentric 3D human pose estimation with a single head-mounted fisheye camera has
recently attracted attention due to its numerous applications in virtual and augmented reality …

Existing volumetric methods for predicting 3D human pose estimation are accurate, but
computationally expensive and optimized for single time-step prediction. We present …

Human pose estimation in sports training is a critical application within Internet of Things
(IoT) environments, leveraging IoT devices to enhance performance analysis and injury …

Existing wearable motion capture methods typically demand tight on-body fixation (often
using straps) for reliable sensing limiting their application in everyday life. In this paper we …

Humans exhibit a remarkable capacity for anticipating the actions of others and planning
their own actions accordingly. In this study, we strive to replicate this ability by addressing …

Human pose estimation is a challenging task due to its structured data sequence nature.
Existing methods primarily focus on pair-wise interaction of body joints, which is insufficient …

Despite progress in human motion capture, existing multi-view methods often face
challenges in estimating the 3D pose and shape of multiple closely interacting people. This …