AffordPose: A Large-scale Dataset of Hand-Object Interactions with Affordance-driven Hand Pose

• URL: http://arxiv.org/abs/2309.08942v1
• Date: Sat, 16 Sep 2023 10:25:28 GMT
• Title: AffordPose: A Large-scale Dataset of Hand-Object Interactions with Affordance-driven Hand Pose
• Authors: Juntao Jian, Xiuping Liu, Manyi Li, Ruizhen Hu, Jian Liu
• Abstract summary: We present AffordPose, a large-scale dataset of hand-object interactions with affordance-driven hand pose. We collect a total of 26.7K hand-object interactions, each including the 3D object shape, the part-level affordance label, and the manually adjusted hand poses. The comprehensive data analysis shows the common characteristics and diversity of hand-object interactions per affordance.
• Score: 16.65196181081623
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: How human interact with objects depends on the functional roles of the target objects, which introduces the problem of affordance-aware hand-object interaction. It requires a large number of human demonstrations for the learning and understanding of plausible and appropriate hand-object interactions. In this work, we present AffordPose, a large-scale dataset of hand-object interactions with affordance-driven hand pose. We first annotate the specific part-level affordance labels for each object, e.g. twist, pull, handle-grasp, etc, instead of the general intents such as use or handover, to indicate the purpose and guide the localization of the hand-object interactions. The fine-grained hand-object interactions reveal the influence of hand-centered affordances on the detailed arrangement of the hand poses, yet also exhibit a certain degree of diversity. We collect a total of 26.7K hand-object interactions, each including the 3D object shape, the part-level affordance label, and the manually adjusted hand poses. The comprehensive data analysis shows the common characteristics and diversity of hand-object interactions per affordance via the parameter statistics and contacting computation. We also conduct experiments on the tasks of hand-object affordance understanding and affordance-oriented hand-object interaction generation, to validate the effectiveness of our dataset in learning the fine-grained hand-object interactions. Project page: https://github.com/GentlesJan/AffordPose.

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