公开(公告)号：US20250157008A1

公开(公告)日：2025-05-15

申请号：US18949522

申请日：2024-11-15

Applicant: Google LLC

Inventor： Tingbo Hou ,  Yanwu Xu ,  Yang Zhao ,  Zhisheng Xiao

IPC: G06T5/60 ,  G06T5/70

Abstract: Provided is a one-step text-to-image generative model, which represents a fusion of GAN and diffusion model elements. In particular, despite the promising outcomes of prior diffusion GAN hybrid models, achieving one-step sampling and extending their utility to text-to-image generation remains a complex challenge. The present disclosure provides a number of innovative techniques to enhance diffusion GAN models, resulting in an ultra-fast text-to-image model capable of producing high-quality images in a single sampling step.

公开(公告)号：US20250165756A1

公开(公告)日：2025-05-22

申请号：US18949875

申请日：2024-11-15

Applicant: Google LLC

Inventor： Yang Zhao ,  Yanwu Xu ,  Zhisheng Xiao ,  Tingbo Hou

IPC: G06N3/0475 ,  G06N3/0464

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating a data item by performing a single-step denoising process using a diffusion model neural network. For example, the data items can be images, videos, audio waveforms, sensor outputs, and so on.