公开(公告)号：US11669566B2

公开(公告)日：2023-06-06

申请号：US17565816

申请日：2021-12-30

Applicant: Adobe Inc.

Inventor： Saeid Motiian ,  Zhe Lin ,  Samarth Gulati ,  Pramod Srinivasan ,  Jose Ignacio Echevarria Vallespi ,  Baldo Antonio Faieta

IPC: G06F16/00 ,  G06F16/583 ,  G06F17/16 ,  G06F16/55 ,  G06F16/532 ,  G06V10/56 ,  G06V10/75 ,  G06V10/762

CPC classification number: G06F16/5838 ,  G06F16/532 ,  G06F16/55 ,  G06F17/16 ,  G06V10/56 ,  G06V10/758 ,  G06V10/763

Abstract: In implementations of multi-resolution color-based image search, an image search system determines a color vector for a query image based on a color histogram of the query image by concatenating two color histograms having different resolutions. The image search system can compute distance measures between the color vector of the query image and color vectors of candidate images. The image search system can select one or more of the candidate images to return based on the distance measures utilizing the distance measures as indication of color similarity of the candidate images to the query image.

公开(公告)号：US20200380027A1

公开(公告)日：2020-12-03

申请号：US16426369

申请日：2019-05-30

Applicant: Adobe Inc.

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

IPC: G06F16/583 ,  G06N3/08 ,  G06N20/00 ,  G06F16/33 ,  G06F16/538 ,  G06F16/532

Abstract: Multi-modal differential search with real-time focus adaptation 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：US12067046B2

公开(公告)日：2024-08-20

申请号：US17932742

申请日：2022-09-16

Applicant: ADOBE INC.

Inventor： Sachin Madhav Kelkar ,  Ajinkya Gorakhnath Kale ,  Alvin Ghouas ,  Baldo Antonio Faieta

IPC: G06F16/54 ,  G06V10/22 ,  G06V10/772

CPC classification number: G06F16/54 ,  G06V10/23 ,  G06V10/772

Abstract: Systems and methods for image exploration are provided. One aspect of the systems and methods includes identifying a set of images; reducing the set of images to obtain a representative set of images that is distributed throughout the set of images by removing a neighbor image based on a proximity of the neighbor image to an image of the representative set of images; arranging the representative set of images in a grid structure using a self-sorting map (SSM) algorithm; and displaying a portion of the representative set of images based on the grid structure.

公开(公告)号：US20230252071A1

公开(公告)日：2023-08-10

申请号：US18302201

申请日：2023-04-18

Applicant: Adobe Inc.

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

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

CPC classification number: G06F16/532 ,  G06F16/51 ,  G06F16/54 ,  G06F16/538 ,  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：US11604822B2

公开(公告)日：2023-03-14

申请号：US16426369

申请日：2019-05-30

Applicant: Adobe Inc.

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

IPC: G06F7/00 ,  G06F16/583 ,  G06N3/084 ,  G06N20/00 ,  G06F16/538 ,  G06F16/532 ,  G06F16/33 ,  G06F3/04855

Abstract: Multi-modal differential search with real-time focus adaptation 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：US11138257B2

公开(公告)日：2021-10-05

申请号：US16745143

申请日：2020-01-16

Applicant: Adobe Inc.

Inventor： Midhun Harikumar ,  Zhe Lin ,  Pramod Srinivasan ,  Jianming Zhang ,  Daniel David Miranda ,  Baldo Antonio Faieta

IPC: G06F16/532 ,  G06F3/0484 ,  G06T7/11 ,  G06F16/538 ,  G06F16/587 ,  G06T7/70

Abstract: Object search techniques for digital images are described. In the techniques described herein, semantic features are extracted on a per-object basis form a digital image. This supports location of objects within digital images and is not limited to semantic features of an entirety of the digital image as involved in conventional image similarity search techniques. This may be combined with indications a location of the object globally with respect to the digital image through use of a global segmentation mask, use of a local segmentation mask to capture post and characteristics of the object itself, and so on.

公开(公告)号：US20210224312A1

公开(公告)日：2021-07-22

申请号：US16745143

申请日：2020-01-16

Applicant: Adobe Inc.

Inventor： Midhun Harikumar ,  Zhe Lin ,  Pramod Srinivasan ,  Jianming Zhang ,  Daniel David Miranda ,  Baldo Antonio Faieta

IPC: G06F16/532 ,  G06F3/0484 ,  G06T7/11 ,  G06T7/70 ,  G06F16/538 ,  G06F16/587

Abstract: Object search techniques for digital images are described. In the techniques described herein, semantic features are extracted on a per-object basis form a digital image. This supports location of objects within digital images and is not limited to semantic features of an entirety of the digital image as involved in conventional image similarity search techniques. This may be combined with indications a location of the object globally with respect to the digital image through use of a global segmentation mask, use of a local segmentation mask to capture post and characteristics of the object itself, and so on.

公开(公告)号：US20240095277A1

公开(公告)日：2024-03-21

申请号：US17932742

申请日：2022-09-16

Applicant: ADOBE INC.

Inventor： Sachin Madhav Kelkar ,  Ajinkya Gorakhnath Kale ,  Alvin Ghouas ,  Baldo Antonio Faieta

IPC: G06F16/54 ,  G06V10/22 ,  G06V10/772

CPC classification number: G06F16/54 ,  G06V10/23 ,  G06V10/772

Abstract: Systems and methods for image exploration are provided. One aspect of the systems and methods includes identifying a set of images; reducing the set of images to obtain a representative set of images that is distributed throughout the set of images by removing a neighbor image based on a proximity of the neighbor image to an image of the representative set of images; arranging the representative set of images in a grid structure using a self-sorting map (SSM) algorithm; and displaying a portion of the representative set of images based on the grid structure.

公开(公告)号：US11934448B2

公开(公告)日：2024-03-19

申请号：US18302201

申请日：2023-04-18

Applicant: Adobe Inc.

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

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

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：US11605019B2

公开(公告)日：2023-03-14

申请号：US16426298

申请日：2019-05-30

Applicant: Adobe Inc.

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

IPC: G06K9/00 ,  G06N20/00 ,  G06K9/62 ,  G06N3/08 ,  G06F16/538 ,  G10L15/22 ,  G06F40/30

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.