US 12,111,880 B2
Face swapping with neural network-based geometry refining
Jacek Krzysztof Naruniec, Windlach (CH); Derek Edward Bradley, Zurich (CH); Paulo Fabiano Urnau Gotardo, Zurich (CH); Leonhard Markus Helminger, Zurich (CH); Christopher Andreas Otto, Zurich (CH); Christopher Richard Schroers, Uster (CH); and Romann Matthew Weber, Uster (CH)
Assigned to DISNEY ENTERPRISES, INC., Burbank, CA (US); and ETH Zurich (Eidgenssische Technische Hochschule Zurich), Zürich (CH)
Filed by DISNEY ENTERPRISES, INC., Burbank, CA (US); and ETH Zürich (Eidgenössische Technische Hochschule Zürich), Zürich (CH)
Filed on Sep. 24, 2021, as Appl. No. 17/484,681.
Claims priority of provisional application 63/191,246, filed on May 20, 2021.
Prior Publication US 2022/0374649 A1, Nov. 24, 2022
Int. Cl. G06T 17/20 (2006.01); G06F 18/21 (2023.01); G06N 3/045 (2023.01); G06N 3/088 (2023.01); G06T 11/00 (2006.01)
CPC G06F 18/21 (2023.01) [G06N 3/045 (2023.01); G06N 3/088 (2013.01); G06T 11/001 (2013.01); G06T 17/20 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30201 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for changing a face within an image, the method comprising:
receiving a first image including a face associated with a first facial identity;
generating, via a machine learning model, at least a first texture map, a second texture map, and a first position map based on the first image, wherein the second texture map represents one or more adjustments to the first texture map; and
rendering a second image including a face associated with a second facial identity based on the first texture map, the first position map, and the second texture map, wherein the second facial identity is different from the first facial identity.