The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 31, 2024

Filed:

Jan. 03, 2023
Applicant:

Autodesk, Inc., San Francisco, CA (US);

Inventors:

Hooman Shayani, Longfield, GB;

Marco Fumero, Rome, IT;

Aditya Sanghi, Toronto, CA;

Assignee:

AUTODESK, INC., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 19/20 (2011.01); G06N 3/0455 (2023.01); G06N 3/0475 (2023.01); G06N 3/08 (2023.01); G06N 3/092 (2023.01); G06T 17/00 (2006.01); G06T 17/10 (2006.01);
U.S. Cl.
CPC ...
G06T 19/20 (2013.01); G06N 3/0455 (2023.01); G06N 3/0475 (2023.01); G06N 3/08 (2013.01); G06N 3/092 (2023.01); G06T 17/00 (2013.01); G06T 17/10 (2013.01); G06T 2210/56 (2013.01); G06T 2219/2021 (2013.01); G06T 2219/2024 (2013.01);
Abstract

One embodiment of the present invention sets forth a technique for training a machine learning model to perform style transfer. The technique includes applying one or more augmentations to a first input three-dimensional (3D) shape to generate a second input 3D shape. The technique also includes generating, via a first set of neural network layers, a style code based on a first latent representation of the first input 3D shape and a second latent representation of the second input 3D shape. The technique further includes generating, via a second set of neural network layers, a first output 3D shape based on the style code and the second latent representation, and performing one or more operations on the first and second sets of neural network layers based on a first loss associated with the first output 3D shape to generate a trained machine learning model.


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