MULTIMODAL CONDITIONAL 3D SHAPE GEOMETRY GENERATION

Number: 20250356586
Published: 2025-11-20
Filed: 2025-05-19
Assignee: DISNEY ENTERPRISES, INC.
Inventors: OTTO; Christopher Andreas et al.
CPC: G06N20/00; G06N3/045; G06N3/084; G06T15/205; G06T17/00; G06T17/10; G06T17/20; G06T19/20; G06T5/60
Verdict: Low Notable software
Source: Google Patents · FreePatentsOnline

The keeper's note

Multimodal generative 3D-shape geometry synthesis technique.

Abstract

One embodiment of the present invention sets forth a technique for generating a geometry for a shape. The technique includes inputting, into a machine learning model, (i) a noise sample and (ii) one or more conditioning inputs. The technique also includes generating, via execution of the machine learning model based on the noise sample and the one or more conditioning inputs, a two-dimensional (2D) position map associated with the shape. The technique further includes generating a three-dimensional (3D) geometry for the shape based on the 2D position map.

Background

BACKGROUND Field of the Various Embodiments

Embodiments of the present disclosure relate generally machine learning and computer vision and, more specifically, to multimodal conditional three-dimensional (3D) shape geometry generation. Description of the Related Art

Realistic digital representations of faces, hands, bodies, and other recognizable objects are required for various computer graphics and computer vision applications. For example, digital representations of real-world deformable objects may be used in virtual scenes of film or television productions, video games, virtual worlds, and/or other environments and/or settings.

Traditionally, three-dimensional (3D) geometries of faces and/or other types of deformable objects have been generated via a time-consuming, iterative, and resource-intensive process involving digital sculpting with 3D modeling tools. For example, a user may spend days to weeks interacting with a 3D modeling tool to manually push, pull, smooth, grab, pinch, and/or otherwise manipulate a 3D geometry of a face. As the user interacts with the 3D geometry, the 3D modeling tool expends significant resources in updating a mesh and/or another 3D representation of the face based on sculpting input from the user, rendering the face to reflect the sculpting input, and/or outputting the rendered face to the user.

To simplify the task of modeling the 3D geometry of a face (or another type of deformable object), a parametric shape m

Claims

1. A computer-implemented method for generating a geometry for a shape, the method comprising: inputting, into a machine learning model, (i) a noise sample and (ii) one or more conditioning inputs; generating, via execution of the machine learning model based on the noise sample and the one or more conditioning inputs, a two-dimensional (2D) position map associated with the shape; and generating a three-dimensional (3D) geometry for the shape based on the 2D position map. || 11. One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of: inputting, into a machine learning model, (i) a noise sample and (ii) one or more conditioning inputs; generating, via execution of the machine learning model based on the noise sample and the one or more conditioning inputs, a two-dimensional (2D) position map associated with a shape; and generating a three-dimensional (3D) geometry for the shape based on the 2D position map. || 20. A system, comprising: one or more memories that store instructions, and one or more processors that are coupled to the one or more memories and, when executing the instructions, are configured to perform the steps of: inputting, into a machine learning model, (i) a noise sample and (ii) one or more conditioning inputs; generating, via execution of the machine learning model based on the noise sample and the one or more conditioning inputs, a two-dimensional (2D) position map associated with a deformable object; and generating a three-dimensional (3D) geometry for the deformable object based on the 2D position map.