SAGA: Stochastic Whole-Body Grasping with Contact
نویسندگان
چکیده
AbstractThe synthesis of human grasping has numerous applications including AR/VR, video games and robotics. While methods have been proposed to generate realistic hand–object interaction for object manipulation, these typically only consider interacting hand alone. Our goal is synthesize whole-body motions. Starting from an arbitrary initial pose, we aim diverse natural motions approach grasp a target in 3D space. This task challenging as it requires modeling both dynamics dexterous finger movements. To this end, propose SAGA (StochAstic Grasping with contAct), framework which consists two key components: (a) Static pose generation. Specifically, multi-task generative model, jointly learn static poses human-object contacts. (b) motion infilling. Given the generated start end respectively, design novel contact-aware infilling module set grasp-oriented We demonstrate effectiveness our method, expressive that randomly placed unseen objects. Code models are available at https://jiahaoplus.github.io/SAGA/saga.html.KeywordsMotion generationWhole-body synthesisHuman-object
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ژورنال
عنوان ژورنال: Lecture Notes in Computer Science
سال: 2022
ISSN: ['1611-3349', '0302-9743']
DOI: https://doi.org/10.1007/978-3-031-20068-7_15