公开(公告)号：US11354792B2

公开(公告)日：2022-06-07

申请号：US16785437

申请日：2020-02-07

Applicant: ADOBE INC.

Inventor： Matthew David Fisher ,  Hung-Yu Tseng ,  Yijun Li ,  Jingwan Lu

IPC: G06T5/50 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20 ,  G06N5/04

Abstract: Technologies for image processing based on a creation workflow for creating a type of images are provided. Both multi-stage image generation as well as multi-stage image editing of an existing image are supported. To accomplish this, one system models the sequential creation stages of the creation workflow. In the backward direction, inference networks can backward transform an image into various intermediate stages. In the forward direction, generation networks can forward transform an earlier-stage image into a later-stage image based on stage-specific operations. Advantageously, this technical solution overcomes the limitations of the single-stage generation strategy with a multi-stage framework to model different types of variation at various creation stages. Resultantly, both novices and seasoned artists can use these technologies to efficiently perform complex artwork creation or editing tasks.

公开(公告)号：US20210248727A1

公开(公告)日：2021-08-12

申请号：US16785437

申请日：2020-02-07

Applicant: ADOBE INC.

Inventor： Matthew David Fisher ,  Hung-Yu Tseng ,  Yijun Li ,  Jingwan Lu

IPC: G06T5/50 ,  G06N20/20 ,  G06N3/08 ,  G06N5/04 ,  G06N3/04

Abstract: This disclosure includes technologies for image processing based on a creation workflow for creating a type of images. The disclosed technologies can support both multi-stage image generation as well as multi-stage image editing of an existing image. To accomplish this, the disclosed system models the sequential creation stages of the creation workflow. In the backward direction, inference networks can backward transform an image into various intermediate stages. In the forward direction, generation networks can forward transform an earlier-stage image into a later-stage image based on stage-specific operations. Advantageously, the disclosed technical solution overcomes the limitations of the single-stage generation strategy with a multi-stage framework to model different types of variation at various creation stages. Resultantly, both novices and seasoned artists can use the disclosed technologies to efficiently perform complex artwork creation or editing tasks.