公开(公告)号：US20240282016A1

公开(公告)日：2024-08-22

申请号：US18172192

申请日：2023-02-21

Applicant: Lemon Inc.

Inventor： Bingchen LIU ,  Qing YAN ,  Yizhe ZHU ,  Xiao YANG

IPC: G06T11/00 ,  G06F3/14 ,  G06Q50/00 ,  G06T3/60 ,  G06V10/70 ,  G06V40/16

CPC classification number: G06T11/00 ,  G06F3/14 ,  G06Q50/01 ,  G06T3/60 ,  G06V10/70 ,  G06V40/161 ,  G06V40/171

Abstract: The present disclosure provides systems and methods for generating a synthesized image of a user with a trained machine learning diffusion model. In one example, a computing system includes one or more processors configured to execute instructions stored in memory to execute a trained machine learning diffusion model including an image encoder, a text encoder, and a diffusion model. The image encoder is configured to receive an image of a user and generate a set of embeddings that semantically describe visual features of the user based at least on the image of the user. The text encoder is configured to receive the set of embeddings and generate an input feature vector based at least on the set of embeddings. The diffusion model is configured to receive the input feature vector and generate a synthesized image of the user based at least on the input feature vector.

公开(公告)号：US20240153151A1

公开(公告)日：2024-05-09

申请号：US18052862

申请日：2022-11-04

Applicant: Lemon Inc.

Inventor： Qing YAN ,  Bingchen LIU ,  Yizhe ZHU ,  Xiao YANG

IPC: G06T11/00 ,  G06F40/40 ,  G06T5/00

CPC classification number: G06T11/00 ,  G06F40/40 ,  G06T5/002

Abstract: Systems and methods are provided that include a processor executing a program to process an initial image through a first diffusion stage to generate a final first stage image, wherein the first diffusion stage includes using a diffusion model, a gradient estimator model smaller than the diffusion model, and a text-image match gradient calculator. The processor further executes the program to process the final first stage image through a second diffusion stage to generate a final second stage image. The second diffusion stage includes, for a second predetermined number of iterations, inputting the final first stage image to through the diffusion model, back-propagate the image through the text-image match gradient calculator to calculate a second stage gradient against the input text, and update the final first stage image by applying the second stage gradient to the final first stage image.