Hand-Centric Motion Refinement for 3D Hand-Object Interaction via Hierarchical Spatial-Temporal Modeling
Yuze Hao, Jianrong Zhang, Tao Zhuo, Fuan Wen, Hehe Fan
Abstract
Hands are the main medium when people interact with the world. Generating proper 3D motion for hand-object interaction is vital for applications such as virtual reality and robotics. Although grasp tracking or object manipulation synthesis can produce coarse hand motion, this kind of motion is inevitably noisy and full of jitter. To address this problem, we propose a data-driven method for coarse motion refinement. First, we design a hand-centric representation to describe the dynamic spatial-temporal relation between hands and objects. Compared to the object-centric representation, our hand-centric representation is straightforward and does not require an ambiguous projection process that converts object-based prediction into hand motion. Second, to capture the dynamic clues of hand-object interaction, we propose a new architecture that models the spatial and temporal structure in a hierarchical manner. Extensive experiments demonstrate that our method outperforms previous methods by a noticeable margin.
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Install the CLIlune papers fulltext 74afeede-c8aa-416b-9e87-7b71aceb018eCited by top-tier papers2
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- Human Motion Diffusion ModelGuy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir et al.ICLR 2023 · 167 citations
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