We present AssemblyHands, a large-scale benchmark dataset with accurate 3D hand pose
annotations, to facilitate the study of egocentric activities with challenging hand-object …

Hand-object interaction understanding and the barely addressed novel view synthesis are
highly desired in the immersive communication, whereas it is challenging due to the high …

Abstract 3D human pose estimation aims to reconstruct the human skeleton of all the
individuals in a scene by detecting several body joints. The creation of accurate and efficient …

Motion capture technology is crucial in various applications like animation, virtual reality and
sports analysis. With the development of deep learning methods, significant progress has …

Abstract 3D human pose estimation has been a long-standing challenge in computer vision
and graphics, where multi-view methods have significantly progressed but are limited by the …

Objective: Marker-based motion capture, considered the gold standard in human motion
analysis, is expensive and requires trained personnel. Advances in inertial sensing and …

To date, little attention has been given to multi-view 3D human mesh estimation, despite real-
life applicability (eg, motion capture, sport analysis) and robustness to single-view …

We present Ego3DPose, a highly accurate binocular egocentric 3D pose reconstruction
system. The binocular egocentric setup offers practicality and usefulness in various …

We introduce UPose3D, a novel approach for multi-view 3D human pose estimation,
addressing challenges in accuracy and scalability. Our method advances existing pose …

In this work we aim to improve the 3D reasoning ability of Transformers in multi-view 3D
human pose estimation. Recent works have focused on end-to-end learning-based …