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Auteurs principaux: Wang, Qiaochu, Xiao, Chufeng, Lau, Manfred, Fu, Hongbo
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2504.20599
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author Wang, Qiaochu
Xiao, Chufeng
Lau, Manfred
Fu, Hongbo
author_facet Wang, Qiaochu
Xiao, Chufeng
Lau, Manfred
Fu, Hongbo
contents Learning-based methods to understand and model hand-object interactions (HOI) require a large amount of high-quality HOI data. One way to create HOI data is to transfer hand poses from a source object to another based on the objects' geometry. However, current methods for transferring hand poses between objects rely on shape matching, limiting the ability to transfer poses across different categories due to differences in their shapes and sizes. We observe that HOI often involves specific semantic parts of objects, which often have more consistent shapes across categories. In addition, constructing size-invariant correspondences between these parts is important for cross-category transfer. Based on these insights, we introduce a novel method PartHOI for part-based HOI transfer. Using a generalized cylinder representation to parameterize an object parts' geometry, PartHOI establishes a robust geometric correspondence between object parts, and enables the transfer of contact points. Given the transferred points, we optimize a hand pose to fit the target object well. Qualitative and quantitative results demonstrate that our method can generalize HOI transfers well even for cross-category objects, and produce high-fidelity results that are superior to the existing methods.
format Preprint
id arxiv_https___arxiv_org_abs_2504_20599
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PartHOI: Part-based Hand-Object Interaction Transfer via Generalized Cylinders
Wang, Qiaochu
Xiao, Chufeng
Lau, Manfred
Fu, Hongbo
Computer Vision and Pattern Recognition
Learning-based methods to understand and model hand-object interactions (HOI) require a large amount of high-quality HOI data. One way to create HOI data is to transfer hand poses from a source object to another based on the objects' geometry. However, current methods for transferring hand poses between objects rely on shape matching, limiting the ability to transfer poses across different categories due to differences in their shapes and sizes. We observe that HOI often involves specific semantic parts of objects, which often have more consistent shapes across categories. In addition, constructing size-invariant correspondences between these parts is important for cross-category transfer. Based on these insights, we introduce a novel method PartHOI for part-based HOI transfer. Using a generalized cylinder representation to parameterize an object parts' geometry, PartHOI establishes a robust geometric correspondence between object parts, and enables the transfer of contact points. Given the transferred points, we optimize a hand pose to fit the target object well. Qualitative and quantitative results demonstrate that our method can generalize HOI transfers well even for cross-category objects, and produce high-fidelity results that are superior to the existing methods.
title PartHOI: Part-based Hand-Object Interaction Transfer via Generalized Cylinders
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2504.20599