公开(公告)号：US12013883B1

公开(公告)日：2024-06-18

申请号：US18200856

申请日：2023-05-23

Applicant: Adobe Inc.

Inventor： Tripti Shukla ,  Vishwa Vinay ,  Srikrishna Karanam ,  Praneetha Vaddamanu ,  Balaji Vasan Srinivasan

IPC: G06F3/0484 ,  G06F16/31 ,  G06F16/332 ,  G06F40/106 ,  G06F40/109 ,  G06F40/186

CPC classification number: G06F16/3323 ,  G06F16/31 ,  G06F40/106 ,  G06F40/109 ,  G06F40/186

Abstract: An illustrator system determines, for each feature of a set of features, a feature representation for an electronic document displayed via a user interface, based on a plurality of elements of the electronic document. The system receives a selection from among the set of features of (1) a query feature and of (2) a target feature and determines, for each replacement template of a set of replacement templates, a compatibility score based on the feature representation for the electronic document determined for the query feature and a target feature representation of the replacement template determined for the target feature, the representations being determined in a joint representation space. The system selects one or more replacement electronic documents based on the determined compatibility scores. The system displays a preview for each replacement electronic document and displays a particular replacement electronic document responsive to receiving a selection of a preview.

公开(公告)号：US20250028911A1

公开(公告)日：2025-01-23

申请号：US18355573

申请日：2023-07-20

Applicant: ADOBE INC.

Inventor： Akshay Ganesh Iyer ,  Nikunj Goyal ,  Kanad Shrikar Pardeshi ,  Pranamya Prashant Kulkarni ,  Abhilasha Sancheti ,  Praneetha Vaddamanu ,  Aparna Garimella ,  Apoorv Umang Saxena ,  Vishwa Vinay

IPC: G06F40/40 ,  G06V10/22 ,  G06V10/44 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82

Abstract: One or more aspects of the method, apparatus, and non-transitory computer readable medium include obtaining an image and a detail level, wherein the detail level comprises a value indicating a level of detail for a description of the image. One or more aspects of the method, apparatus, and non-transitory computer readable medium further include identifying a set of regions for the image based on the detail level using a machine learning model, and generating a description for the image based on the set of regions, wherein an amount of detail in the description is based on the detail level.

公开(公告)号：US20240119646A1

公开(公告)日：2024-04-11

申请号：US18541377

申请日：2023-12-15

Applicant: Adobe Inc.

Inventor： Paridhi Maheshwari ,  Vishwa Vinay ,  Shraiysh Vaishay ,  Praneetha Vaddamanu ,  Nihal Jain ,  Dhananjay Bhausaheb Raut

IPC: G06T11/00 ,  G06F40/30 ,  G06V10/40

CPC classification number: G06T11/001 ,  G06F40/30 ,  G06V10/40 ,  G06T2207/10024 ,  G06T2207/20081

Abstract: Digital image text editing techniques as implemented by an image processing system are described that support increased user interaction in the creation and editing of digital images through understanding a content creator's intent as expressed using text. In one example, a text user input is received by a text input module. The text user input describes a visual object and a visual attribute, in which the visual object specifies a visual context of the visual attribute. A feature representation generated by a text-to-feature system using a machine-learning module based on the text user input. The feature representation is passed to an image editing system to edit a digital object in a digital image, e.g., by applying a texture to an outline of the digital object within the digital image.

公开(公告)号：US11915343B2

公开(公告)日：2024-02-27

申请号：US17111819

申请日：2020-12-04

Applicant: ADOBE INC.

Inventor： Paridhi Maheshwari ,  Vishwa Vinay ,  Dhananjay Raut ,  Nihal Jain ,  Praneetha Vaddamanu ,  Shraiysh Vaishay

IPC: G06T11/00 ,  G06F40/253 ,  G06F40/30 ,  G06V10/56 ,  G06F18/24 ,  G06F18/214 ,  G06N3/08 ,  G06N3/044

CPC classification number: G06T11/001 ,  G06F18/214 ,  G06F18/24 ,  G06F40/253 ,  G06F40/30 ,  G06N3/044 ,  G06N3/08 ,  G06V10/56

Abstract: Systems and methods for color representation are described. Embodiments of the inventive concept are configured to receive an attribute-object pair including a first term comprising an attribute label and a second term comprising an object label, encode the attribute-object pair to produce encoded features using a neural network that orders the first term and the second term based on the attribute label and the object label, and generate a color profile for the attribute-object pair based on the encoded features, wherein the color profile is based on a compositional relationship between the first term and the second term.

公开(公告)号：US11887217B2

公开(公告)日：2024-01-30

申请号：US17079844

申请日：2020-10-26

Applicant: Adobe Inc.

Inventor： Paridhi Maheshwari ,  Vishwa Vinay ,  Shraiysh Vaishay ,  Praneetha Vaddamanu ,  Nihal Jain ,  Dhananjay Bhausaheb Raut

IPC: G06T11/00 ,  G06F40/30 ,  G06V10/40

CPC classification number: G06T11/001 ,  G06F40/30 ,  G06V10/40 ,  G06T2207/10024 ,  G06T2207/20081

Abstract: Digital image text editing techniques as implemented by an image processing system are described that support increased user interaction in the creation and editing of digital images through understanding a content creator's intent as expressed using text. In one example, a text user input is received by a text input module. The text user input describes a visual object and a visual attribute, in which the visual object specifies a visual context of the visual attribute. A feature representation generated by a text-to-feature system using a machine-learning module based on the text user input. The feature representation is passed to an image editing system to edit a digital object in a digital image, e.g., by applying a texture to an outline of the digital object within the digital image.

公开(公告)号：US20220130078A1

公开(公告)日：2022-04-28

申请号：US17079844

申请日：2020-10-26

Applicant: Adobe Inc.

Inventor： Paridhi Maheshwari ,  Vishwa Vinay ,  Shraiysh Vaishay ,  Praneetha Vaddamanu ,  Nihal Jain ,  Dhananjay Bhausaheb Raut

IPC: G06T11/00 ,  G06F40/30 ,  G06K9/46

Abstract: Digital image text editing techniques as implemented by an image processing system are described that support increased user interaction in the creation and editing of digital images through understanding a content creator's intent as expressed using text. In one example, a text user input is received by a text input module. The text user input describes a visual object and a visual attribute, in which the visual object specifies a visual context of the visual attribute. A feature representation generated by a text-to-feature system using a machine-learning module based on the text user input. The feature representation is passed to an image editing system to edit the digital object in the digital image, e.g., by applying a texture to an outline of the digital object within the digital image.