公开(公告)号：US11860932B2

公开(公告)日：2024-01-02

申请号：US17337801

申请日：2021-06-03

Applicant: ADOBE INC.

Inventor： Paridhi Maheshwari ,  Ritwick Chaudhry ,  Vishwa Vinay

IPC: G06F16/50 ,  G06F16/55 ,  G06F16/56 ,  G06F16/538 ,  G06F16/583

CPC classification number: G06F16/55 ,  G06F16/538 ,  G06F16/56 ,  G06F16/583 ,  G06F16/5854

Abstract: Systems and methods for image processing are described. One or more embodiments of the present disclosure identify an image including a plurality of objects, generate a scene graph of the image including a node representing an object and an edge representing a relationship between two of the objects, generate a node vector for the node, wherein the node vector represents semantic information of the object, generate an edge vector for the edge, wherein the edge vector represents semantic information of the relationship, generate a scene graph embedding based on the node vector and the edge vector using a graph convolutional network (GCN), and assign metadata to the image based on the scene graph embedding.

公开(公告)号：US20220277136A1

公开(公告)日：2022-09-01

申请号：US17188302

申请日：2021-03-01

Applicant: Adobe Inc.

Inventor： Sumit Shekhar ,  Vedant Raval ,  Tripti Shukla ,  Simarpreet singh Saluja ,  Paridhi Maheshwari ,  Divyam Gupta

IPC: G06F40/186 ,  G06F40/106 ,  G06N3/04 ,  G06K9/62

Abstract: Certain embodiments involve a template-based redesign of documents based on the contents of documents. For instance, a computing system selects a template for modifying an input document. To do so, the computing system uses a generative adversarial network to generate an interpolated layout image from an input layout image, which represents the input document, and a template layout image, which represents the selected template. The computing system matches the input element to an interpolated element from the interpolated layout image. The computing system generates an output document by, for example, modifying a layout of the input document to match the interpolated layout image, such as by fitting the input element into a shape of the interpolated element.

公开(公告)号：US20210342389A1

公开(公告)日：2021-11-04

申请号：US16865888

申请日：2020-05-04

Applicant: Adobe Inc.

Inventor： Paridhi Maheshwari ,  Vishwa Vinay ,  Manoj Ghuhan Arivazhagan

IPC: G06F16/583 ,  G06N20/00 ,  G06F16/532 ,  G06F16/58 ,  G06F16/54

Abstract: The disclosed techniques include at least one computer-implemented method performed by a system. The system can receive a textual query and process query features of the textual query to identify a color profile indicative of a color intent of the query. The system can identify candidate images that at least partially match the desired content and color intent of the query. The system can further order candidate images based in part on a similarity of a candidate color profile for each candidate image with the identified color profile of the query, and output image data indicative of the ordered set of candidate images.

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：US11416684B2

公开(公告)日：2022-08-16

申请号：US16784145

申请日：2020-02-06

Applicant: Adobe Inc.

Inventor： Paridhi Maheshwari ,  Harsh Deshpande ,  Diviya Singh ,  Natwar Modani ,  Srinivas Saurab Sirpurkar

IPC: G06F40/137 ,  G06F40/237 ,  G06F40/279 ,  G06F40/30 ,  G06F40/216 ,  G06V30/416

Abstract: Techniques are described for intelligently identifying concept labels for a set of multiple documents where the identified concept labels are representative of and semantically relevant to the information contained by the set of documents. The technique includes extracting semantic units (e.g., paragraphs) from the set of documents and determining concept labels applicable to the semantic units based on relevance scores computed for the concept labels. The technique includes determining an initial set of concept labels for the set of documents based on the applicable concept labels. The technique further includes obtaining a reference hierarchy associated with the reference set of concept labels and determining a final set of concept labels for the set of documents using a reference hierarchy, the initial set of concept labels, and the relevance scores. The technique includes outputting information identifying the final set of concept labels for the set of documents.

公开(公告)号：US20210192549A1

公开(公告)日：2021-06-24

申请号：US16722626

申请日：2019-12-20

Applicant: Adobe Inc.

Inventor： Atanu R. Sinha ,  Paridhi Maheshwari ,  Ayalur Vedpuriswar Lakshmy ,  Tanay Anand ,  Vishal Manohar Jain

IPC: G06Q30/02

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for easily, accurately, and efficiently determining a personalized market share of a user with a company versus that of its competitors using only focal company's own clickstream data. For instance, the disclosed systems can infer a mapping of purchases to product categories from clickstream data of a company and use the mappings to generate a dataset of observable conversions (with interconversion times) for one or more product categories. Then, the disclosed systems can utilize models for a category level interconversion time and for transition probabilities of a user to determine a personalized market share and an interconversion time for an individual user (between the company and competitors of the company). In addition, the disclosed systems can generate graphical user interfaces that efficiently provide personalized customer statistics based at least on the determined personalized market share and interconversion times for the individual user.

公开(公告)号：US10665030B1

公开(公告)日：2020-05-26

申请号：US16247235

申请日：2019-01-14

Applicant: Adobe Inc.

Inventor： Sumit Shekhar ,  Paridhi Maheshwari ,  Monisha J ,  Kundan Krishna ,  Amrit Singhal ,  Kush Kumar Singh

IPC: G06T19/00 ,  G06F40/40

Abstract: A natural language scene description is converted into a scene that is rendered in three dimensions by an augmented reality (AR) display device. Text-to-AR scene conversion allows a user to create an AR scene visualization through natural language text inputs that are easily created and well-understood by the user. The user can, for instance, select a pre-defined natural language description of a scene or manually enter a custom natural language description. The user can also select a physical real-world surface on which the AR scene is to be rendered. The AR scene is then rendered using the augmented reality display device according to its natural language description using 3D models of objects and humanoid characters with associated animations of those characters, as well as from extensive language-to-visual datasets. Using the display device, the user can move around the real-world environment and experience the AR scene from different angles.

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.

公开(公告)号：US20210248322A1

公开(公告)日：2021-08-12

申请号：US16784000

申请日：2020-02-06

Applicant: Adobe Inc.

Inventor： Natwar Modani ,  Srinivas Saurab Sirpurkar ,  Paridhi Maheshwari ,  Harsh Deshpande ,  Diviya Singh

IPC: G06F40/30 ,  G06F40/216 ,  G06K9/00 ,  G06F9/30

Abstract: A technique for intelligently identifying concept labels for a text fragment where the identified concept labels are representative of and semantically relevant to the information contained by the text fragment is provided. The technique includes determining, using a knowledge base storing information for a reference set of concept labels, a first subset of concept labels that are relevant to the information contained by the text fragment. The technique includes ordering the first subset of concept labels according to their relevance scores and performing dependency analysis on the ordered list of concept labels. Based on the dependency analysis, the technique includes identifying concept labels for a text fragment that are more independent (e.g., more distinct and non-overlapping) of each other, representative of and semantically relevant to the information represented by the text fragment.