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dc.contributor.authorGhosh, Aninditaen_US
dc.contributor.authorDabral, Rishabhen_US
dc.contributor.authorGolyanik, Vladislaven_US
dc.contributor.authorTheobalt, Christianen_US
dc.contributor.authorSlusallek, Philippen_US
dc.contributor.editorMyszkowski, Karolen_US
dc.contributor.editorNiessner, Matthiasen_US
dc.date.accessioned2023-05-03T06:09:12Z
dc.date.available2023-05-03T06:09:12Z
dc.date.issued2023
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14739
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14739
dc.description.abstractCan we make virtual characters in a scene interact with their surrounding objects through simple instructions? Is it possible to synthesize such motion plausibly with a diverse set of objects and instructions? Inspired by these questions, we present the first framework to synthesize the full-body motion of virtual human characters performing specified actions with 3D objects placed within their reach. Our system takes textual instructions specifying the objects and the associated 'intentions' of the virtual characters as input and outputs diverse sequences of full-body motions. This contrasts existing works, where full-body action synthesis methods generally do not consider object interactions, and human-object interaction methods focus mainly on synthesizing hand or finger movements for grasping objects. We accomplish our objective by designing an intent-driven fullbody motion generator, which uses a pair of decoupled conditional variational auto-regressors to learn the motion of the body parts in an autoregressive manner. We also optimize the 6-DoF pose of the objects such that they plausibly fit within the hands of the synthesized characters. We compare our proposed method with the existing methods of motion synthesis and establish a new and stronger state-of-the-art for the task of intent-driven motion synthesis.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleIMoS: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactionsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersHuman Object Interaction
dc.description.volume42
dc.description.number2
dc.identifier.doi10.1111/cgf.14739
dc.identifier.pages1-12
dc.identifier.pages12 pages


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License