US 12,079,927 B2
Light estimation using neural networks
Gleb Dmukhin, Kyiv (UA); Egor Nemchinov, London (GB); and Yurii Volkov, Kyiv (UA)
Assigned to Snap Inc., Santa Monica, CA (US)
Filed by Snap Inc., Santa Monica, CA (US)
Filed on Oct. 20, 2021, as Appl. No. 17/506,248.
Claims priority of provisional application 63/133,191, filed on Dec. 31, 2020.
Prior Publication US 2022/0207819 A1, Jun. 30, 2022
Int. Cl. G06T 15/50 (2011.01); G06N 3/08 (2023.01); G06V 10/60 (2022.01)
CPC G06T 15/506 (2013.01) [G06N 3/08 (2013.01); G06V 10/60 (2022.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
receiving an input image with first lighting properties;
processing the input image, comprising a first plurality of pixels, using a convolutional neural network to generate a second plurality of pixels corresponding to the first plurality of pixels, the second plurality of pixels comprising an estimate of the first lighting properties, the estimate comprising estimates of at least one of: hue values, saturation values, and brightness values of the first plurality of pixels;
modifying the input image within a region with an augmentation to generate a modified input image, the augmentation having second lighting properties; and
changing the second lighting properties of the augmentation in the modified input image based on pixels of the second plurality of pixels corresponding to a same position within the first plurality of pixels as the region within the modified input image.