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ICCV 2023

ContactGen: Generative Contact Modeling for Grasp Generation

Shaowei Liu, Yang Zhou, Jimei Yang, Saurabh Gupta, Shenlong Wang

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摘要

This paper presents a novel object-centric contact representation ContactGen for hand-object interaction. The ContactGen comprises 3 components: a contact map indicates the contact location, a part map represents the contact hand part, and a direction map tells the contact direction within each part. Given an input object, we propose a conditional generative model to predict ContactGen and adopt model-based optimization to predict diverse and geometrically feasible grasps. Experimental results demonstrate our method can generate high-fidelity and diverse human grasps for various objects.