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 …

Seizure events can manifest as transient disruptions in the control of movements which may
be organized in distinct behavioral sequences, accompanied or not by other observable …

Hand gesture is one of the most efficient and natural interfaces in current human–computer
interaction (HCI) systems. Despite the great progress achieved in hand gesture-based HCI …

We interact with the world with our hands and see it through our own (egocentric)
perspective. A holistic 3D understanding of such interactions from egocentric views is …

We aim to improve the performance of regressing hand keypoints and segmenting pixel-
level hand masks under new imaging conditions (eg., outdoors) when we only have labeled …

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 …

In this paper, we tackle the problem of detailed hand-object 3D reconstruction from
monocular video with unknown objects, for applications where the required accuracy and …

Hand pose estimation from egocentric video has broad implications across various domains,
including human-computer interaction, assistive technologies, activity recognition, and …

We present a contrastive learning framework based on in-the-wild hand images tailored for
pre-training 3D hand pose estimators, dubbed HandCLR. Pre-training on large-scale …

Effective hand gestures are crucial for human-machine interactions, and recent
advancements in neural networks offer promising avenues for efficient hand pose …