US 11,748,928 B2
Face anonymization in digital images
Yang Yang, Santa Clara, CA (US); Zhixin Shu, San Jose, CA (US); Shabnam Ghadar, Menlo Park, CA (US); Jingwan Lu, Santa Clara, CA (US); Jakub Fiser, Seattle, WA (US); Elya Schechtman, Seattle, WA (US); Cameron Y. Smith, Santa Cruz, CA (US); Baldo Antonio Faieta, San Francisco, CA (US); and Alex Charles Filipkowski, San Francisco, CA (US)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Nov. 10, 2020, as Appl. No. 17/94,093.
Prior Publication US 2022/0148243 A1, May 12, 2022
Int. Cl. G06T 11/60 (2006.01); G06F 21/62 (2013.01); G06F 16/56 (2019.01); G06F 16/532 (2019.01)
CPC G06T 11/60 (2013.01) [G06F 16/532 (2019.01); G06F 16/56 (2019.01); G06F 21/6254 (2013.01); G06T 2200/24 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving, by a processing device, a target digital image having a target face;
obtaining, by the processing device, a reference digital image including a reference face as a result of a digital image search performed based at least in part on the target face by:
computing a similarity score between the target face and the reference face; and
comparing a pose of the target face to a pose of the reference face;
generating, by the processing device, a target encoding of the target face and a reference encoding of the reference face using a machine-learning model;
generating, by the processing device, a mixed encoding by combining a portion of the target encoding and a portion of the reference encoding that represents features of the target face mixed with features of the reference face;
generating, by the processing device, a mixed face using a machine-learning model from the mixed encoding; and
forming, by the processing device, an edited target digital image by replacing the target face with the mixed face.