US 12,136,203 B2
Photo relighting using deep neural networks and confidence learning
Tiancheng Sun, Mountain View, CA (US); Yun-Ta Tsai, Los Gatos, CA (US); and Jonathan Barron, Alameda, CA (US)
Assigned to Google LLC, Mountain View, CA (US)
Filed by Google LLC, Mountain View, CA (US)
Filed on Aug. 22, 2023, as Appl. No. 18/236,583.
Application 18/236,583 is a continuation of application No. 17/260,364, granted, now 11,776,095, previously published as PCT/US2019/025205, filed on Apr. 1, 2019.
Claims priority of provisional application 62/749,081, filed on Oct. 22, 2018.
Claims priority of provisional application 62/735,506, filed on Sep. 24, 2018.
Prior Publication US 2023/0401681 A1, Dec. 14, 2023
Int. Cl. G06T 5/00 (2024.01); G06T 5/94 (2024.01); G06T 15/50 (2011.01)
CPC G06T 5/94 (2024.01) [G06T 15/506 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
receiving a training dataset comprising a plurality of images, wherein each image of the plurality of images is associated with a corresponding lighting model, wherein a given lighting model corresponding to a given image is indicative of a location of one or more environmental light sources with reference to an object in the given image;
training, based on the training dataset, a neural network by:
receiving, by a computing device, an input image and data about a target lighting model,
predicting an initial lighting model associated with the input image, and
predicting a relighting of the input image by replacing the initial lighting model with the target lighting model; and
providing the trained neural network.