公开(公告)号：US20250078327A1

公开(公告)日：2025-03-06

申请号：US18457895

申请日：2023-08-29

Applicant: Adobe Inc.

Inventor： Zhipeng Bao ,  Yijun Li ,  Krishna Kumar Singh

IPC: G06T11/00 ,  G06V10/82

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize a text-image alignment loss to train a diffusion model to generate digital images from input text. In particular, in some embodiments, the disclosed systems generate a prompt noise representation form a text prompt with a first text concept and a second text concept using a denoising step of a diffusion neural network. Further, in some embodiments, the disclosed systems generate a first concept noise representation from the first text concept and a second concept noise representation from the second text concept. Moreover, the disclosed systems combine the first and second concept noise representation to generate a combined concept noise representation. Accordingly, in some embodiments, by comparing the combined concept noise representation and the prompt noise representation, the disclosed systems modify parameters of the diffusion neural network.