公开(公告)号：US12014452B2

公开(公告)日：2024-06-18

申请号：US18449604

申请日：2023-08-14

Applicant: Adobe Inc.

Inventor： Akhilesh Kumar ,  Baldo Faieta ,  Piotr Walczyszyn ,  Ratheesh Kalarot ,  Archie Bagnall ,  Shabnam Ghadar ,  Wei-An Lin ,  Cameron Smith ,  Christian Cantrell ,  Patrick Hebron ,  Wilson Chan ,  Jingwan Lu ,  Holger Winnemoeller ,  Sven Olsen

IPC: G06T11/60 ,  G06N3/04 ,  G06T11/20

CPC classification number: G06T11/60 ,  G06N3/04 ,  G06T11/203

Abstract: The present disclosure describes systems, methods, and non-transitory computer readable media for detecting user interactions to edit a digital image from a client device and modify the digital image for the client device by using a web-based intermediary that modifies a latent vector of the digital image and an image modification neural network to generate a modified digital image from the modified latent vector. In response to user interaction to modify a digital image, for instance, the disclosed systems modify a latent vector extracted from the digital image to reflect the requested modification. The disclosed systems further use a latent vector stream renderer (as an intermediary device) to generate an image delta that indicates a difference between the digital image and the modified digital image. The disclosed systems then provide the image delta as part of a digital stream to a client device to quickly render the modified digital image.

公开(公告)号：US11887216B2

公开(公告)日：2024-01-30

申请号：US17455796

申请日：2021-11-19

Applicant: ADOBE INC.

Inventor： Ratheesh Kalarot ,  Timothy M. Converse ,  Shabnam Ghadar ,  John Thomas Nack ,  Jingwan Lu ,  Elya Shechtman ,  Baldo Faieta ,  Akhilesh Kumar

IPC: G06T5/00 ,  G06T11/00 ,  G06N3/08 ,  G06V40/16

CPC classification number: G06T11/00 ,  G06N3/08 ,  G06V40/168 ,  G06V40/172

Abstract: The present disclosure describes systems and methods for image processing. Embodiments of the present disclosure include an image processing apparatus configured to generate modified images (e.g., synthetic faces) by conditionally changing attributes or landmarks of an input image. A machine learning model of the image processing apparatus encodes the input image to obtain a joint conditional vector that represents attributes and landmarks of the input image in a vector space. The joint conditional vector is then modified, according to the techniques described herein, to form a latent vector used to generate a modified image. In some cases, the machine learning model is trained using a generative adversarial network (GAN) with a normalization technique, followed by joint training of a landmark embedding and attribute embedding (e.g., to reduce inference time).

公开(公告)号：US20230386114A1

公开(公告)日：2023-11-30

申请号：US18449604

申请日：2023-08-14

Applicant: Adobe Inc.

Inventor： Akhilesh Kumar ,  Baldo Faieta ,  Piotr Walczyszyn ,  Ratheesh Kalarot ,  Archie Bagnall ,  Shabnam Ghadar ,  Wei-An Lin ,  Cameron Smith ,  Christian Cantrell ,  Patrick Hebron ,  Wilson Chan ,  Jingwan Lu ,  Holger Winnemoeller ,  Sven Olsen

IPC: G06T11/60 ,  G06T11/20 ,  G06N3/04

CPC classification number: G06T11/60 ,  G06N3/04 ,  G06T11/203

Abstract: The present disclosure describes systems, methods, and non-transitory computer readable media for detecting user interactions to edit a digital image from a client device and modify the digital image for the client device by using a web-based intermediary that modifies a latent vector of the digital image and an image modification neural network to generate a modified digital image from the modified latent vector. In response to user interaction to modify a digital image, for instance, the disclosed systems modify a latent vector extracted from the digital image to reflect the requested modification. The disclosed systems further use a latent vector stream renderer (as an intermediary device) to generate an image delta that indicates a difference between the digital image and the modified digital image. The disclosed systems then provide the image delta as part of a digital stream to a client device to quickly render the modified digital image.

公开(公告)号：US20230076196A1

公开(公告)日：2023-03-09

申请号：US17466699

申请日：2021-09-03

Applicant: ADOBE INC.

Inventor： Akhilesh Kumar ,  Ratheesh Kalarot ,  Baldo Faieta ,  Shabnam Ghadar

IPC: G06T11/60 ,  G06N3/04 ,  G06T3/40 ,  H04L29/06

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for editing images using a web-based intermediary between a user interface on a client device and an image editing neural network(s) (e.g., a generative adversarial network) on a server(s). The present image editing system supports multiple users in the same software container, advanced concurrency of projection and transformation of the same image, clubbing transformation requests from several users hosted in the same software container, and smooth display updates during a progressive projection.

公开(公告)号：US20220253990A1

公开(公告)日：2022-08-11

申请号：US17172744

申请日：2021-02-10

Applicant: ADOBE INC.

Inventor： Akhilesh Kumar ,  Zhe Lin ,  Baldo Faieta

IPC: G06T5/20 ,  G06N3/04 ,  G06K9/62 ,  G06T7/00

Abstract: The present disclosure describes systems and methods for image enhancement. Embodiments of the present disclosure provide an image enhancement system with a feedback mechanism that provides quantifiable image enhancement information. An image enhancement system may include a discriminator network that determines the quality of the media object. In cases where the discriminator network determines that the media object has a low image quality score (e.g., an image quality score below a quality threshold), the image enhancement system may perform enhancement on the media object using an enhancement network (e.g., using an enhancement network that includes a generative neural network or a generative adversarial network (GAN) model). The discriminator network may then generate an enhancement score for the enhanced media object that may be provided to the user as a feedback mechanism (e.g., where the enhancement score generated by the discriminator network quantifies the enhancement performed by the enhancement network).

公开(公告)号：US20210406302A1

公开(公告)日：2021-12-30

申请号：US16910440

申请日：2020-06-24

Applicant: Adobe Inc.

Inventor： Akhilesh Kumar ,  Zhe Lin ,  Ratheesh Kalarot ,  Jinrong Xie ,  Jianming Zhang ,  Baldo Antonio Faieta ,  Alex Charles Filipkowski

IPC: G06F16/55 ,  G06F16/538 ,  G06N20/20 ,  G06N3/02

Abstract: Multidimensional digital content search techniques are described that support an ability of a computing device to perform search with increased granularity and flexibility over conventional techniques. In one example, a control is implemented by a computing device that defines a multidimensional (e.g., two-dimensional) continuous space. Locations in the multidimensional continuous space are usable to different search criteria through different weights applied to the criteria associated with the axes. Therefore, user interaction with this control may be used to define a location and corresponding coordinates that may act as weights to the search criteria in order to perform a search of digital content through use of a single user input.

公开(公告)号：US12141952B2

公开(公告)日：2024-11-12

申请号：US17957639

申请日：2022-09-30

Applicant: Adobe Inc.

Inventor： Akhilesh Kumar ,  Zhe Lin ,  William Lawrence Marino

IPC: G06N3/08 ,  G06N5/04 ,  G06T7/00

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for detecting and classifying an exposure defect in an image using neural networks trained via a limited amount of labeled training images. An image may be applied to a first neural network to determine whether the images includes an exposure defect. Detected defective image may be applied to a second neural network to determine an exposure defect classification for the image. The exposure defect classification can includes severe underexposure, medium underexposure, mild underexposure, mild overexposure, medium overexposure, severe overexposure, and/or the like. The image may be presented to a user along with the exposure defect classification.

公开(公告)号：US11853348B2

公开(公告)日：2023-12-26

申请号：US16910440

申请日：2020-06-24

Applicant: Adobe Inc.

Inventor： Akhilesh Kumar ,  Zhe Lin ,  Ratheesh Kalarot ,  Jinrong Xie ,  Jianming Zhang ,  Baldo Antonio Faieta ,  Alex Charles Filipkowski

IPC: G06F16/532 ,  G06F16/583 ,  G06F16/55 ,  G06F16/538 ,  G06N3/02 ,  G06N20/20

CPC classification number: G06F16/532 ,  G06F16/538 ,  G06F16/55 ,  G06F16/583 ,  G06N3/02 ,  G06N20/20

Abstract: Multidimensional digital content search techniques are described that support an ability of a computing device to perform search with increased granularity and flexibility over conventional techniques. In one example, a control is implemented by a computing device that defines a multidimensional (e.g., two-dimensional) continuous space. Locations in the multidimensional continuous space are usable to different search criteria through different weights applied to the criteria associated with the axes. Therefore, user interaction with this control may be used to define a location and corresponding coordinates that may act as weights to the search criteria in order to perform a search of digital content through use of a single user input.

公开(公告)号：US20230162407A1

公开(公告)日：2023-05-25

申请号：US17455796

申请日：2021-11-19

Applicant: ADOBE INC.

Inventor： Ratheesh Kalarot ,  Timothy M. Converse ,  Shabnam Ghadar ,  John Thomas Nack ,  Jingwan Lu ,  Elya Shechtman ,  Baldo Faieta ,  Akhilesh Kumar

IPC: G06T11/00 ,  G06K9/00 ,  G06N3/08

CPC classification number: G06T11/00 ,  G06K9/00288 ,  G06K9/00268 ,  G06N3/08

Abstract: The present disclosure describes systems and methods for image processing. Embodiments of the present disclosure include an image processing apparatus configured to generate modified images (e.g., synthetic faces) by conditionally changing attributes or landmarks of an input image. A machine learning model of the image processing apparatus encodes the input image to obtain a joint conditional vector that represents attributes and landmarks of the input image in a vector space. The joint conditional vector is then modified, according to the techniques described herein, to form a latent vector used to generate a modified image. In some cases, the machine learning model is trained using a generative adversarial network (GAN) with a normalization technique, followed by joint training of a landmark embedding and attribute embedding (e.g., to reduce inference time).

公开(公告)号：US20230024955A1

公开(公告)日：2023-01-26

申请号：US17957639

申请日：2022-09-30

Applicant: Adobe Inc.

Inventor： Akhilesh Kumar ,  Zhe Lin ,  William Lawrence Marino

IPC: G06T7/00 ,  G06N3/08 ,  G06N5/04

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for detecting and classifying an exposure defect in an image using neural networks trained via a limited amount of labeled training images. An image may be applied to a first neural network to determine whether the images includes an exposure defect. Detected defective image may be applied to a second neural network to determine an exposure defect classification for the image. The exposure defect classification can includes severe underexposure, medium underexposure, mild underexposure, mild overexposure, medium overexposure, severe overexposure, and/or the like. The image may be presented to a user along with the exposure defect classification.