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Can we make virtual characters in a scene interact with their surroundingobjects through simple instructions? Is it possible to synthesize such motionplausibly with a diverse set of objects and instructions? Inspired by thesequestions, we present the first framework to synthesize the full-body motion ofvirtual human characters performing specified actions with 3D objects placedwithin their reach. Our system takes textual instructions specifying theobjects and the associated intentions of the virtual characters as input andoutputs diverse sequences of full-body motions. This contrasts existing works,where full-body action synthesis methods generally do not consider objectinteractions, and human-object interaction methods focus mainly on synthesizinghand or finger movements for grasping objects. We accomplish our objective bydesigning an intent-driven fullbody motion generator, which uses a pair ofdecoupled conditional variational auto-regressors to learn the motion of thebody parts in an autoregressive manner. We also optimize the 6-DoF pose of theobjects such that they plausibly fit within the hands of the synthesizedcharacters. We compare our proposed method with the existing methods of motionsynthesis and establish a new and stronger state-of-the-art for the task ofintent-driven motion synthesis.

IMos: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactions