公开(公告)号：US12165284B2

公开(公告)日：2024-12-10

申请号：US17655663

申请日：2022-03-21

Applicant: Adobe Inc.

Inventor： He Zhang ,  Jianming Zhang ,  Jose Ignacio Echevarria Vallespi ,  Kalyan Sunkavalli ,  Meredith Payne Stotzner ,  Yinglan Ma ,  Zhe Lin ,  Elya Shechtman ,  Frederick Mandia

IPC: G06V10/00 ,  G06T5/50 ,  G06T7/194 ,  G06T7/90 ,  G06T11/00

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that implement a dual-branched neural network architecture to harmonize composite images. For example, in one or more implementations, the transformer-based harmonization system uses a convolutional branch and a transformer branch to generate a harmonized composite image based on an input composite image and a corresponding segmentation mask. More particularly, the convolutional branch comprises a series of convolutional neural network layers followed by a style normalization layer to extract localized information from the input composite image. Further, the transformer branch comprises a series of transformer neural network layers to extract global information based on different resolutions of the input composite image. Utilizing a decoder, the transformer-based harmonization system combines the local information and the global information from the corresponding convolutional branch and transformer branch to generate a harmonized composite image.

公开(公告)号：US10706512B2

公开(公告)日：2020-07-07

申请号：US15452112

申请日：2017-03-07

Applicant: ADOBE INC.

Inventor： Yinglan Ma ,  Sylvain Philippe Paris ,  Chih-Yao Hsieh

IPC: G06K9/40 ,  G06T5/00 ,  G06T5/50 ,  H04N5/232 ,  H04N5/235 ,  H04N9/64 ,  H04N9/04 ,  H04N9/76

Abstract: Methods and systems are provided for adjusting the brightness of images. In some implementations, an exposure bracketed set of input images produced by a camera is received. A brightness adjustment is determined for at least one input image from the set of input images. The determined brightness adjustment is applied to the input image. An output image is produced by exposure fusion from the set of input images, using the input image having the determined brightness adjustment. The output image is transmitted where, the transmitting causes display of the output image on a user device.

公开(公告)号：US12148074B2

公开(公告)日：2024-11-19

申请号：US17503671

申请日：2021-10-18

Applicant: Adobe Inc.

Inventor： He Zhang ,  Jeya Maria Jose Valanarasu ,  Jianming Zhang ,  Jose Ignacio Echevarria Vallespi ,  Kalyan Sunkavalli ,  Yilin Wang ,  Yinglan Ma ,  Zhe Lin ,  Zijun Wei

IPC: G06T11/60 ,  G06F3/04842 ,  G06F3/04845 ,  G06N3/08 ,  G06V10/40 ,  G06V10/75

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating harmonized digital images utilizing an object-to-object harmonization neural network. For example, the disclosed systems implement, and learn parameters for, an object-to-object harmonization neural network to combine a style code from a reference object with features extracted from a target object. Indeed, the disclosed systems extract a style code from a reference object utilizing a style encoder neural network. In addition, the disclosed systems generate a harmonized target object by applying the style code of the reference object to a target object utilizing an object-to-object harmonization neural network.

公开(公告)号：US20230122623A1

公开(公告)日：2023-04-20

申请号：US17503671

申请日：2021-10-18

Applicant: Adobe Inc.

Inventor： He Zhang ,  Jeya Maria Jose Valanarasu ,  Jianming Zhang ,  Jose Ignacio Echevarria Vallespi ,  Kalyan Sunkavalli ,  Yilin Wang ,  Yinglan Ma ,  Zhe Lin ,  Zijun Wei

IPC: G06T11/60 ,  G06F3/0484 ,  G06K9/46 ,  G06K9/62 ,  G06N3/08

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating harmonized digital images utilizing an object-to-object harmonization neural network. For example, the disclosed systems implement, and learn parameters for, an object-to-object harmonization neural network to combine a style code from a reference object with features extracted from a target object. Indeed, the disclosed systems extract a style code from a reference object utilizing a style encoder neural network. In addition, the disclosed systems generate a harmonized target object by applying the style code of the reference object to a target object utilizing an object-to-object harmonization neural network.

公开(公告)号：US11307881B1

公开(公告)日：2022-04-19

申请号：US17095290

申请日：2020-11-11

Applicant: Adobe Inc.

Inventor： Ripul Bhutani ,  Oliver Markus Michael Brdiczka ,  Doo Soon Kim ,  Aliakbar Darabi ,  Yinglan Ma

IPC: G06F3/0482 ,  G06F9/451 ,  G06N5/02 ,  G06F16/23

Abstract: In implementations of systems for generating suggestions with knowledge graph embedding vectors, a computing device implements a suggestion system to receive input data describing user interactions with an application for editing digital content. The suggestion system generates input embedding vectors based on the user interactions with the application and determines an item based on the input embedding vectors and knowledge graph embedding vectors generated from nodes of a knowledge graph describing a tutorial for editing digital content. The suggestion system generates an indication of the item for display in a user interface of a display device.

公开(公告)号：US20200312298A1

公开(公告)日：2020-10-01

申请号：US16366904

申请日：2019-03-27

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Zahra Rahimi ,  Yinglan Ma ,  Seokhwan Kim ,  Franck Dernoncourt

IPC: G10L15/06 ,  G06F3/16 ,  G06F3/0482 ,  G06F3/0484 ,  G06F17/24 ,  G10L15/22 ,  G10L15/18 ,  G06N20/00

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate ground truth annotations of target utterances in digital image editing dialogues in order to create a state-driven training data set. In particular, in one or more embodiments, the disclosed systems utilize machine and user defined tags, machine learning model predictions, and user input to generate a ground truth annotation that includes frame information in addition to intent, attribute, object, and/or location information. In at least one embodiment, the disclosed systems generate ground truth annotations in conformance with an annotation ontology that results in fast and accurate digital image editing dialogue annotation.

公开(公告)号：US20200175975A1

公开(公告)日：2020-06-04

申请号：US16205126

申请日：2018-11-29

Applicant: Adobe Inc.

Inventor： Sarah Kong ,  Yinglan Ma ,  Hyunghwan Byun ,  Chih-Yao Hsieh

IPC: G10L15/22 ,  G06F3/16 ,  G06F3/0484 ,  G06T11/60

Abstract: This application relates generally to modifying visual data based on audio commands and more specifically, to performing complex operations that modify visual data based on one or more audio commands. In some embodiments, a computer system may receive an audio input and identify an audio command based on the audio input. The audio command may be mapped to one or more operations capable of being performed by a multimedia editing application. The computer system may perform the one or more operations to edit to received multimedia data.

公开(公告)号：US20230298148A1

公开(公告)日：2023-09-21

申请号：US17655663

申请日：2022-03-21

Applicant: Adobe Inc.

Inventor： He Zhang ,  Jianming Zhang ,  Jose Ignacio Echevarria Vallespi ,  Kalyan Sunkavalli ,  Meredith Payne Stotzner ,  Yinglan Ma ,  Zhe Lin ,  Elya Shechtman ,  Frederick Mandia

IPC: G06T5/50 ,  G06T7/194 ,  G06T7/90 ,  G06T11/00

CPC classification number: G06T5/50 ,  G06T7/194 ,  G06T7/90 ,  G06T11/001 ,  G06T2207/20084 ,  G06T2207/20212 ,  G06T2200/24 ,  G06T2207/20092 ,  G06T2207/20016 ,  G06T2207/20081 ,  G06T2207/30168

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that implement a dual-branched neural network architecture to harmonize composite images. For example, in one or more implementations, the transformer-based harmonization system uses a convolutional branch and a transformer branch to generate a harmonized composite image based on an input composite image and a corresponding segmentation mask. More particularly, the convolutional branch comprises a series of convolutional neural network layers followed by a style normalization layer to extract localized information from the input composite image. Further, the transformer branch comprises a series of transformer neural network layers to extract global information based on different resolutions of the input composite image. Utilizing a decoder, the transformer-based harmonization system combines the local information and the global information from the corresponding convolutional branch and transformer branch to generate a harmonized composite image.

公开(公告)号：US11257491B2

公开(公告)日：2022-02-22

申请号：US16205126

申请日：2018-11-29

Applicant: Adobe Inc.

Inventor： Sarah Kong ,  Yinglan Ma ,  Hyunghwan Byun ,  Chih-Yao Hsieh

IPC: G10L15/22 ,  G06F3/16 ,  G06T11/60 ,  G06F3/0484 ,  G06F3/04845

Abstract: This application relates generally to modifying visual data based on audio commands and more specifically, to performing complex operations that modify visual data based on one or more audio commands. In some embodiments, a computer system may receive an audio input and identify an audio command based on the audio input. The audio command may be mapped to one or more operations capable of being performed by a multimedia editing application. The computer system may perform the one or more operations to edit to received multimedia data.

公开(公告)号：US11100917B2

公开(公告)日：2021-08-24

申请号：US16366904

申请日：2019-03-27

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Zahra Rahimi ,  Yinglan Ma ,  Seokhwan Kim ,  Franck Dernoncourt

IPC: G10L15/06 ,  G06F3/16 ,  G06F3/0482 ,  G06N20/00 ,  G10L15/22 ,  G10L15/18 ,  G06F3/0484 ,  G06F40/169

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate ground truth annotations of target utterances in digital image editing dialogues in order to create a state-driven training data set. In particular, in one or more embodiments, the disclosed systems utilize machine and user defined tags, machine learning model predictions, and user input to generate a ground truth annotation that includes frame information in addition to intent, attribute, object, and/or location information. In at least one embodiment, the disclosed systems generate ground truth annotations in conformance with an annotation ontology that results in fast and accurate digital image editing dialogue annotation.