SCENE-AWARE SYNTHETIC HUMAN MOTION GENERATION USING NEURAL NETWORKS

Abstract: a motion diffusion model may be pre-trained on motion data, and a scene-aware component (e.g., one or more layers of a neural network) may be connected and used to extract and inject a representation of scene information into the pre-trained motion diffusion model. for example, to predict orientations of joint waypoints along a path through a particular 3d scene, a scene-aware input channel that accepts a representation of the 3d structure of the scene may be added to a pre-trained motion diffusion model. to predict orientations of joint waypoints along a path that interacts with a 3d object in the 3d scene, a scene-aware input channel that accepts a representation of the 3d object and/or a surface thereof may be added to a pre-trained motion diffusion model. as such, the resulting scene-aware motion diffusion model(s) may be tuned on motion-scene data and used to generate human motion.

Inventor(s): Hongwei YI, Davis REMPE, Xue Bin PENG, Sanja FIDLER

CPC Classification: G06T13/40 (of characters, e.g. humans, animals or virtual beings)

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