US 11,893,763 B2
Generating modified digital images utilizing a global and spatial autoencoder
Taesung Park, Albany (CA); Richard Zhang, San Francisco, CA (US); Oliver Wang, Seattle, WA (US); Junyan Zhu, Cambridge, MA (US); Jingwan Lu, Santa Clara, CA (US); Elya Shechtman, Seattle, WA (US); and Alexei A Efros, Berkley, CA (US)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Nov. 22, 2022, as Appl. No. 18/058,163.
Application 18/058,163 is a continuation of application No. 16/874,399, filed on May 14, 2020, granted, now 11,544,880.
Prior Publication US 2023/0102055 A1, Mar. 30, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 9/00 (2006.01); G06N 3/08 (2023.01); G06T 3/40 (2006.01)
CPC G06T 9/002 (2013.01) [G06N 3/08 (2013.01); G06T 3/4046 (2013.01); G06T 2200/24 (2013.01); G06T 2210/36 (2013.01); G06T 2219/2024 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause a computing device to:
extract from a first digital image, utilizing an encoder neural network comprising a first set of blocks for encoding global features and a second set of blocks for encoding spatial features, a spatial code comprising features representing a geometric layout of the first digital image by extracting intermediate features using the second set of blocks to upsample features extracted from the first set of blocks;
extract from a second digital image, utilizing the encoder neural network, a global code comprising features representing overall style properties of the second digital image; and
generate a modified digital image by combining the spatial code with the global code utilizing a generator neural network.