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 …

Abstract Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain
gap between a labeled source dataset and an unlabelled target dataset for regression …

The task of weakly supervised temporal sentence grounding aims at finding the
corresponding temporal moments of a language description in the video, given video …

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 …

The pursuit of accurate 3D hand pose estimation stands as a keystone for understanding
human activity in the realm of egocentric vision. The majority of existing estimation methods …

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 …

In this survey, we present a systematic review of 3D hand pose estimation from the
perspective of efficient annotation and learning. 3D hand pose estimation has been an …

Contrastive Language-Image Pre-training (CLIP) starts to emerge in many computer vision
tasks and has achieved promising performance. However, it remains underexplored …

Existing cross-domain keypoint detection methods always require accessing the source data
during adaptation, which may violate the data privacy law and pose serious security …

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 …