公开(公告)号：US20220180572A1

公开(公告)日：2022-06-09

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 ,  G06K9/46 ,  G06K9/62 ,  G06F40/253 ,  G06F40/30 ,  G06N3/04 ,  G06N3/08

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：US20190294732A1

公开(公告)日：2019-09-26

申请号：US15928288

申请日：2018-03-22

Applicant: ADOBE INC.

Inventor： BALAJI VASAN SRINIVASAN ,  RAJAT CHATURVEDI ,  TANYA GOYAL ,  PARIDHI MAHESHWARI ,  ANISH VALLIYATH MONSY ,  ABHILASHA SANCHETI

IPC: G06F17/30

Abstract: A framework is provided for constructing enterprise-specific knowledge bases from enterprise-specific data that includes structured and unstructured data. Relationships between entities that match known relationships are identified for each of a plurality of tuples included in the structured data. Where possible, relationships between entities that match known relationships also are identified for tuples included in the unstructured data. If matching relationships between entities that cannot be identified for tuples in the unstructured data, extracted relationships are sequentially clustered to similar relationships and a relationship is assigned to the clustered tuples. An enterprise-specific knowledge graph is constructed from the structured-data-tuples and their identified relationships, the unstructured-data-tuples where the relationships could be mapped to a known relationship and their identified relationships, and the unstructured-data-tuples that could not be mapped to a known relationship and their assigned relationships. The knowledge graph is enriched with any information determined to be missing therefrom.

公开(公告)号：US20220391433A1

公开(公告)日：2022-12-08

申请号：US17337801

申请日：2021-06-03

Applicant: ADOBE INC.

Inventor： PARIDHI MAHESHWARI ,  Ritwick Chaudhry ,  Vishwa Vinay

IPC: G06F16/56 ,  G06F16/538 ,  G06F16/583 ,  G06K9/46 ,  G06N3/08

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.