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Generating and modifying digital images using a joint feature style latent space of a generative neural network

Grant US12586270B2 Kind: B2 Mar 24, 2026

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

G06T 11/60 G06N 3/045 G06N 3/092 G06N 3/0464 G06N 3/0475 G06N 3/084

Filing Date

2022-03-21

Application No.

17655739

Claims

20