We present an approach that can reconstruct hands in 3D from monocular input. Our
approach for Hand Mesh Recovery HaMeR follows a fully transformer-based architecture …

The two-hand interaction is one of the most challenging signals to analyze due to the self-
similarity, complicated articulations, and occlusions of hands. Although several datasets …

Signed distance functions (SDFs) is an attractive framework that has recently shown
promising results for 3D shape reconstruction from images. SDFs seamlessly generalize to …

Despite recent achievements, existing 3D interacting hands recovery methods have shown
results mainly on motion capture (MoCap) environments, not on in-the-wild (ITW) ones. This …

Abstract 3D interacting hand pose estimation from a single RGB image is a challenging task,
due to serious self-occlusion and inter-occlusion towards hands, confusing similar …

Reconstructing interacting hands from monocular images is indispensable in AR/VR
applications. Most existing solutions rely on the accurate localization of each skeleton joint …

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 …

Understanding dynamic hand motions and actions from egocentric RGB videos is a
fundamental yet challenging task due to self-occlusion and ambiguity. To address occlusion …

Reconstructing interacting hands from a single RGB image is a very challenging task. On the
one hand, severe mutual occlusion and similar local appearance between two hands …

The current interacting hand (IH) datasets are relatively simplistic in terms of background
and texture, with hand joints being annotated by a machine annotator, which may result in …