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 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 …

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 …

This paper investigates data-free class-incremental learning (DFCIL) for hand gesture
recognition from 3D skeleton sequences. In this class-incremental learning (CIL) setting …

Continuous mid-air hand gesture recognition based on captured hand pose streams is
fundamental for human-computer interaction, particularly in AR/VR. However, many of the …

Enable neural networks to capture 3D geometrical-aware features is essential in multi-view
based vision tasks. Previous methods usually encode the 3D information of multi-view …

Full-body ego-pose estimation from head and hand poses alone has become an active area
of research to power articulate avatar representation on headset-based platforms. However …

Recent advancements in 3D hand pose estimation have shown promising results, but its
effectiveness has primarily relied on the availability of large-scale annotated datasets, the …

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 …

We propose a novel transformer-based framework that reconstructs two high fidelity hands
from multi-view RGB images. Unlike existing hand pose estimation methods, where one …