US 12,287,847 B2
Systems and methods for artificial facial image generation conditioned on demographic information
Tung Thanh Tran, Bradenton, FL (US); Dongwook Shin, Potomac, MD (US); Jefferson D. Hoye, Arlington, VA (US); and Matthew R. Ehlers, Raleigh, NC (US)
Assigned to IDS TECHNOLOGY LLC, Arlington, VA (US)
Filed by IDS Technology, LLC, Arlington, VA (US)
Filed on Nov. 11, 2021, as Appl. No. 17/524,475.
Claims priority of provisional application 63/112,323, filed on Nov. 11, 2020.
Prior Publication US 2022/0147769 A1, May 12, 2022
Int. Cl. G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 18/2431 (2023.01); G06T 11/00 (2006.01)
CPC G06F 18/214 (2023.01) [G06F 18/2431 (2023.01); G06T 11/00 (2013.01)] 21 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
analyzing, by a computing device, a plurality of facial images to determine a plurality of demographic labels associated with each facial image of the plurality of facial images;
training a model based upon, at least in part, the plurality of demographic labels associated with each facial image of the plurality of facial images, wherein the model is a generative adversarial network (GAN) with a generator and a discriminator, wherein the generator includes a label embedding layer that processes a one-hot encoded vector for each of the demographic labels, wherein the discriminator includes an affine layer that processes a tensor for each of the demographic labels;
receiving an input of at least a portion of the plurality of demographic labels; and
providing an artificially generated facial image for display that is generated based upon, at least in part, the model and the input.