Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …

Due to the mutual occlusion, severe scale variation, and complex spatial distribution, the
current multi-person mesh recovery methods cannot produce accurate absolute body poses …

Single-stage models for multi-person pose estimation have garnered significant attention
due to their streamlined approach in generating person position localization and body …

We present WorldPose, a novel dataset for advancing research in multi-person global pose
estimation in the wild, featuring footage from the 2022 FIFA World Cup. While previous …

Existing multi-person human reconstruction approaches mainly focus on recovering
accurate poses or avoiding penetration but overlook the modeling of close interactions. In …

The realm of Absolute 3D Human Pose Estimation (3DHPE) via a calibrated monocular
camera has undergone thorough exploration within the domain of deep learning. However …

This paper aims to reconstruct hundreds of people's 3D poses, shapes, and locations from a
single image with unknown camera parameters. Due to the small and highly varying 2D …

Tailoring remains a timeless technique that guarantees clothing fit each unique body
perfectly in an era where precision and personalization are vital. Concurrently, 3D …

To address the issues of low accuracy in existing 3D human pose estimation (HPE) methods
and the limited level of details in Labanotation, we propose an extended Labanotation …