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:
Aug. 17, 2021

Filed:

Jul. 19, 2018
Applicant:

Facebook Technologies, Llc, Menlo Park, CA (US);

Inventors:

Douglas Robert Lanman, Bellevue, WA (US);

Matthew Steven Chapman, Redmond, WA (US);

Alexander Jobe Fix, Seattle, WA (US);

Anton S. Kaplanyan, Redmond, WA (US);

Lei Xiao, Redmond, WA (US);

Assignee:

Facebook Technologies, LLC, Menlo Park, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/557 (2017.01); G06N 5/04 (2006.01); G06T 7/11 (2017.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06T 7/557 (2017.01); G06N 3/08 (2013.01); G06N 5/046 (2013.01); G06T 7/11 (2017.01);
Abstract

In one embodiment, a system may access a training sample that includes training images and corresponding training depth maps of a scene, with the training images being associated with different predetermined viewpoints of the scene. The system may generate elemental images of the scene by processing the training images and the training depth maps using a machine-learning model. The elemental images are associated with more viewpoints of the scene than the predetermined viewpoints associated with the training images. The system may update the machine-learning model based on a comparison between the generated elemental images of the scene and target elemental images that are each associated with a predetermined viewpoint. The updated machine-learning model is configured to generate elemental images of a scene of interest based on input images and corresponding depth maps of the scene of interest from different viewpoints.


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