Zobrazeno 1 - 10
of 1 017 594
pro vyhledávání: '"Hand, P"'
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 images achieves promising results in various tasks, but prior 3D hand pose pre
Externí odkaz:
http://arxiv.org/abs/2409.09714
Hand-Object Interaction (HOI) is gaining significant attention, particularly with the creation of numerous egocentric datasets driven by AR/VR applications. However, third-person view HOI has received less attention, especially in terms of datasets.
Externí odkaz:
http://arxiv.org/abs/2409.09319
Autor:
Rahimi, Farnaz, Badamchizadeh, Mohammad Ali, Sîmpetru, Raul C., Ghaemi, Sehraneh, Eskofier, Bjoern M., Del Vecchio, Alessandro
In myoelectric control, simultaneous control of multiple degrees of freedom can be challenging due to the dexterity of the human hand. Numerous studies have focused on hand functionality, however, they only focused on a few degrees of freedom. In thi
Externí odkaz:
http://arxiv.org/abs/2410.23986
We present PiMForce, a novel framework that enhances hand pressure estimation by leveraging 3D hand posture information to augment forearm surface electromyography (sEMG) signals. Our approach utilizes detailed spatial information from 3D hand poses
Externí odkaz:
http://arxiv.org/abs/2410.23629
Dexterous in-hand manipulation offers significant potential to enhance robotic manipulator capabilities. This paper presents a comprehensive study on custom sensors and parallel gripper hardware specifically designed for in-hand slippage control. The
Externí odkaz:
http://arxiv.org/abs/2410.19660
A human-shaped robotic hand offers unparalleled versatility and fine motor skills, enabling it to perform a broad spectrum of tasks with precision, power and robustness. Across the paleontological record and animal kingdom we see a wide range of alte
Externí odkaz:
http://arxiv.org/abs/2410.18633
Human hand and head movements are the most pervasive input modalities in extended reality (XR) and are significant for a wide range of applications. However, prior works on hand and head modelling in XR only explored a single modality or focused on s
Externí odkaz:
http://arxiv.org/abs/2410.16430
To advance autonomous dexterous manipulation, we propose a hybrid control method that combines the relative advantages of a fine-tuned Vision-Language-Action (VLA) model and diffusion models. The VLA model provides language commanded high-level plann
Externí odkaz:
http://arxiv.org/abs/2410.14022
Due to the increasing use of virtual avatars, the animation of head-hand interactions has recently gained attention. To this end, we present a novel volumetric and physics-based interaction simulation. In contrast to previous work, our simulation inc
Externí odkaz:
http://arxiv.org/abs/2410.13503
Autor:
Grison, Agnese, Pereda, Jaime Ibanez, Muceli, Silvia, Kundu, Aritra, Baracat, Farah, Indiveri, Giacomo, Donati, Elisa, Farina, Dario
Decoding nervous system activity is a key challenge in neuroscience and neural interfacing. In this study, we propose a novel neural decoding system that enables unprecedented large-scale sampling of muscle activity. Using micro-electrode arrays with
Externí odkaz:
http://arxiv.org/abs/2410.11016