公开(公告)号：US12079269B2

公开(公告)日：2024-09-03

申请号：US18104848

申请日：2023-02-02

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Antonio Motiian

IPC: G06F16/00 ,  G06F16/538 ,  G06F16/583 ,  G06F18/21 ,  G06F18/22 ,  G06N3/08 ,  G06N20/00 ,  G06V10/82 ,  G06V10/94 ,  G06V30/19 ,  G06V30/262 ,  G06F40/30 ,  G10L15/22

CPC classification number: G06F16/583 ,  G06F16/538 ,  G06F18/21 ,  G06F18/22 ,  G06N3/08 ,  G06N20/00 ,  G06V10/82 ,  G06V10/945 ,  G06V30/19147 ,  G06V30/1916 ,  G06V30/19173 ,  G06V30/274 ,  G06F40/30 ,  G10L15/22

Abstract: Visually guided machine-learning language model and embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. In one example, a model is trained to support a visually guided machine-learning embedding space that supports visual intuition as to “what” is represented by text. The visually guided language embedding space supported by the model, once trained, may then be used to support visual intuition as part of a variety of functionality. In one such example, the visually guided language embedding space as implemented by the model may be leveraged as part of a multi-modal differential search to support search of digital images and other digital content with real-time focus adaptation which overcomes the challenges of conventional techniques.

公开(公告)号：US11775578B2

公开(公告)日：2023-10-03

申请号：US17398317

申请日：2021-08-10

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Motiian

IPC: G06K9/62 ,  G06K9/72 ,  G06F16/535 ,  G06N20/00 ,  G06V30/262 ,  G06F18/40 ,  G06F18/214 ,  G06V30/19 ,  G06V10/82 ,  G06V10/94 ,  G06F3/0482

CPC classification number: G06F16/535 ,  G06F18/2148 ,  G06F18/40 ,  G06N20/00 ,  G06V10/82 ,  G06V10/945 ,  G06V30/1916 ,  G06V30/19147 ,  G06V30/19173 ,  G06V30/274 ,  G06F3/0482

Abstract: Text-to-visual machine learning embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. These techniques include use of query-based training data which may expand availability and types of training data usable to train a model. Generation of negative digital image samples is also described that may increase accuracy in training the model using machine learning. A loss function is also described that also supports increased accuracy and computational efficiency by losses separately, e.g., between positive or negative sample embeddings a text embedding.

公开(公告)号：US11748928B2

公开(公告)日：2023-09-05

申请号：US17094093

申请日：2020-11-10

Applicant: Adobe Inc.

Inventor： Yang Yang ,  Zhixin Shu ,  Shabnam Ghadar ,  Jingwan Lu ,  Jakub Fiser ,  Elya Schechtman ,  Cameron Y. Smith ,  Baldo Antonio Faieta ,  Alex Charles Filipkowski

IPC: G06T11/60 ,  G06F21/62 ,  G06F16/56 ,  G06F16/532

CPC classification number: G06T11/60 ,  G06F16/532 ,  G06F16/56 ,  G06F21/6254 ,  G06T2200/24

Abstract: Face anonymization techniques are described that overcome conventional challenges to generate an anonymized face. In one example, a digital object editing system is configured to generate an anonymized face based on a target face and a reference face. As part of this, the digital object editing system employs an encoder as part of machine learning to extract a target encoding of the target face image and a reference encoding of the reference face. The digital object editing system then generates a mixed encoding from the target and reference encodings. The mixed encoding is employed by a machine-learning model of the digital object editing system to generate a mixed face. An object replacement module is used by the digital object editing system to replace the target face in the target digital image with the mixed face.

公开(公告)号：US20230185844A1

公开(公告)日：2023-06-15

申请号：US18104848

申请日：2023-02-02

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Antonio Motiian

IPC: G06F16/583 ,  G06N20/00 ,  G06N3/08 ,  G06F16/538 ,  G06F18/21 ,  G06F18/22 ,  G06V30/19 ,  G06V30/262 ,  G06V10/82 ,  G06V10/94

CPC classification number: G06F16/583 ,  G06N20/00 ,  G06N3/08 ,  G06F16/538 ,  G06F18/21 ,  G06F18/22 ,  G06V30/19147 ,  G06V30/1916 ,  G06V30/19173 ,  G06V30/274 ,  G06V10/82 ,  G06V10/945 ,  G10L15/22

Abstract: Visually guided machine-learning language model and embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. In one example, a model is trained to support a visually guided machine-learning embedding space that supports visual intuition as to “what” is represented by text. The visually guided language embedding space supported by the model, once trained, may then be used to support visual intuition as part of a variety of functionality. In one such example, the visually guided language embedding space as implemented by the model may be leveraged as part of a multi-modal differential search to support search of digital images and other digital content with real-time focus adaptation which overcomes the challenges of conventional techniques.

公开(公告)号：US11663264B2

公开(公告)日：2023-05-30

申请号：US16785410

申请日：2020-02-07

Applicant: Adobe Inc.

Inventor： Pramod Srinivasan ,  Zhe Lin ,  Samarth Gulati ,  Saeid Motiian ,  Midhun Harikumar ,  Baldo Antonio Faieta ,  Alex C. Filipkowski

IPC: G06F16/532 ,  G06F16/583 ,  G06F16/538 ,  G06F40/30 ,  G06F16/51 ,  G06F16/54

CPC classification number: G06F16/532 ,  G06F16/51 ,  G06F16/538 ,  G06F16/54 ,  G06F16/583 ,  G06F40/30

Abstract: Keyword localization digital image search techniques are described. These techniques support an ability to indicate “where” a corresponding keyword is to be expressed with respect to a layout in a respective digital image resulting from a search query. The search query may also include an indication of a size of the keyword as expressed in the digital image, a number of instances of the keyword, and so forth. Additionally, the techniques and systems as described herein support real time search through use of keyword signatures.

公开(公告)号：US11288727B2

公开(公告)日：2022-03-29

申请号：US16673774

申请日：2019-11-04

Applicant: Adobe Inc.

Inventor： Zeke Koch ,  Baldo Antonio Faieta ,  Jen-Chan Chien ,  Mark M. Randall ,  Olivier Sirven ,  Philipp Koch ,  Dennis G. Nicholson

IPC: G06F7/00 ,  G06Q30/06 ,  G06F21/16 ,  G06Q50/18 ,  G06F16/9535 ,  G06F16/583 ,  G06F16/58

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.

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：US20210248177A1

公开(公告)日：2021-08-12

申请号：US16785410

申请日：2020-02-07

Applicant: Adobe Inc.

Inventor： Pramod Srinivasan ,  Zhe Lin ,  Samarth Gulati ,  Saeid Motiian ,  Midhun Harikumar ,  Baldo Antonio Faieta ,  Alex C. Filipkowski

IPC: G06F16/532 ,  G06F40/30 ,  G06F16/51 ,  G06F16/583 ,  G06F16/538 ,  G06F16/54

Abstract: Keyword localization digital image search techniques are described. These techniques support an ability to indicate “where” a corresponding keyword is to be expressed with respect to a layout in a respective digital image resulting from a search query. The search query may also include an indication of a size of the keyword as expressed in the digital image, a number of instances of the keyword, and so forth. Additionally, the techniques and systems as described herein support real time search through use of keyword signatures.

公开(公告)号：US20200065875A1

公开(公告)日：2020-02-27

申请号：US16673774

申请日：2019-11-04

Applicant: Adobe Inc.

Inventor： Zeke Koch ,  Baldo Antonio Faieta ,  Jen-Chan Chien ,  Mark M. Randall ,  Olivier Sirven ,  Philipp Koch ,  Dennis G. Nicholson

IPC: G06Q30/06 ,  G06F21/16 ,  G06Q50/18 ,  G06F16/9535 ,  G06F16/583 ,  G06F16/58

Abstract: Content creation suggestion techniques are described. In one or more implementations, techniques are implemented to generate suggestions that are usable to guide creative professionals in the creation of content such as images, video, sound, multimedia, and so forth. A variety of techniques are usable to generate suggestions for the content professionals. In a first such example, suggestions are based on shared characteristics of images obtained by users of a content sharing service, e.g., licensed by the users. In another example, suggestions are generated by the content sharing service based on keywords used to locate the images. In a further example, suggestions are generated based on data described communications performed using social network services. In yet another example, recognition of failure of search is used to generate suggestions. A variety of other examples are also contemplated and described herein.