Generating and modifying digital images using a joint feature style latent space of a generative neural network
Assignee
Adobe Inc.
Inventors
Hui Qu, Baldo Faieta, Cameron Smith, Elya Shechtman, Jingwan Lu, Ratheesh Kalarot, Richard Zhang, Saeid Motiian, Shabnam Ghadar, Wei-An Lin
Abstract
The present disclosure relates to systems, non-transitory computer-readable media, and methods for latent-based editing of digital images using a generative neural network. In particular, in one or more embodiments, the disclosed systems perform latent-based editing of a digital image by mapping a feature tensor and a set of style vectors for the digital image into a joint feature style space. In one or more implementations, the disclosed systems apply a joint feature style perturbation and/or modification vectors within the joint feature style space to determine modified style vectors and a modified feature tensor. Moreover, in one or more embodiments the disclosed systems generate a modified digital image utilizing a generative neural network from the modified style vectors and the modified feature tensor.
CPC Classifications
Filing Date
2022-03-21
Application No.
17655739
Claims
20