GB2585972B - Utilizing object attribute detection models to automatically select instances of detected objects in images - Google Patents

Utilizing object attribute detection models to automatically select instances of detected objects in images Download PDF

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Publication number
GB2585972B
GB2585972B GB2005714.7A GB202005714A GB2585972B GB 2585972 B GB2585972 B GB 2585972B GB 202005714 A GB202005714 A GB 202005714A GB 2585972 B GB2585972 B GB 2585972B
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United Kingdom
Prior art keywords
images
automatically select
detected objects
object attribute
detection models
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
GB2005714.7A
Other versions
GB202005714D0 (en
GB2585972A (en
Inventor
Cohen Scott
Lin Zhe
Ling Mingyang
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Adobe Inc
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Adobe Inc
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Filing date
Publication date
Priority claimed from US16/518,810 external-priority patent/US11631234B2/en
Priority claimed from US16/518,850 external-priority patent/US11468550B2/en
Priority claimed from US16/518,880 external-priority patent/US11107219B2/en
Priority claimed from US16/518,795 external-priority patent/US11302033B2/en
Application filed by Adobe Inc filed Critical Adobe Inc
Publication of GB202005714D0 publication Critical patent/GB202005714D0/en
Publication of GB2585972A publication Critical patent/GB2585972A/en
Application granted granted Critical
Publication of GB2585972B publication Critical patent/GB2585972B/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/53—Querying
    • G06F16/535—Filtering based on additional data, e.g. user or group profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
    • G06F18/24133—Distances to prototypes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/60—Editing figures and text; Combining figures or text
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/56—Extraction of image or video features relating to colour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
GB2005714.7A 2019-07-22 2020-04-20 Utilizing object attribute detection models to automatically select instances of detected objects in images Active GB2585972B (en)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US16/518,810 US11631234B2 (en) 2019-07-22 2019-07-22 Automatically detecting user-requested objects in images
US16/518,850 US11468550B2 (en) 2019-07-22 2019-07-22 Utilizing object attribute detection models to automatically select instances of detected objects in images
US16/518,880 US11107219B2 (en) 2019-07-22 2019-07-22 Utilizing object attribute detection models to automatically select instances of detected objects in images
US16/518,795 US11302033B2 (en) 2019-07-22 2019-07-22 Classifying colors of objects in digital images

Publications (3)

Publication Number Publication Date
GB202005714D0 GB202005714D0 (en) 2020-06-03
GB2585972A GB2585972A (en) 2021-01-27
GB2585972B true GB2585972B (en) 2022-09-21

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Family Applications (3)

Application Number Title Priority Date Filing Date
GB2004362.6A Active GB2586678B (en) 2019-07-22 2020-03-26 Utilizing multiple object detection models to automatically select user-requested objects in images
GB2005704.8A Active GB2585971B (en) 2019-07-22 2020-04-20 Classifying colors of objects in digital images
GB2005714.7A Active GB2585972B (en) 2019-07-22 2020-04-20 Utilizing object attribute detection models to automatically select instances of detected objects in images

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GB2004362.6A Active GB2586678B (en) 2019-07-22 2020-03-26 Utilizing multiple object detection models to automatically select user-requested objects in images
GB2005704.8A Active GB2585971B (en) 2019-07-22 2020-04-20 Classifying colors of objects in digital images

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Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20230368339A1 (en) * 2022-05-13 2023-11-16 Adobe Inc. Object class inpainting in digital images utilizing class-specific inpainting neural networks

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080069444A1 (en) * 2006-09-19 2008-03-20 Adobe Systems Incorporated Image mask generation
US20150170005A1 (en) * 2013-12-16 2015-06-18 Adobe Systems Incorporated Semantic object selection
US20150213058A1 (en) * 2014-01-24 2015-07-30 Amol Ashok Ambardekar Adaptable image search with computer vision assistance
WO2017007626A1 (en) * 2015-07-09 2017-01-12 Qualcomm Incorporated Context-based priors for object detection in images
US20170287137A1 (en) * 2016-03-31 2017-10-05 Adobe Systems Incorporated Utilizing deep learning for boundary-aware image segmentation
US20190130229A1 (en) * 2017-10-31 2019-05-02 Adobe Inc. Deep salient content neural networks for efficient digital object segmentation

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6469706B1 (en) * 1999-11-16 2002-10-22 International Business Machines Corporation Method and apparatus for detecting regions belonging to a specified color surface in an unsegmented image
US7398201B2 (en) * 2001-08-14 2008-07-08 Evri Inc. Method and system for enhanced data searching
CN103366178B (en) * 2012-03-30 2017-12-29 北京百度网讯科技有限公司 A kind of method and apparatus for being used to carry out target image color classification
US10192129B2 (en) 2015-11-18 2019-01-29 Adobe Systems Incorporated Utilizing interactive deep learning to select objects in digital visual media
US10424064B2 (en) 2016-10-18 2019-09-24 Adobe Inc. Instance-level semantic segmentation system
US10216766B2 (en) 2017-03-20 2019-02-26 Adobe Inc. Large-scale image tagging using image-to-topic embedding

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080069444A1 (en) * 2006-09-19 2008-03-20 Adobe Systems Incorporated Image mask generation
US20150170005A1 (en) * 2013-12-16 2015-06-18 Adobe Systems Incorporated Semantic object selection
US20150213058A1 (en) * 2014-01-24 2015-07-30 Amol Ashok Ambardekar Adaptable image search with computer vision assistance
WO2017007626A1 (en) * 2015-07-09 2017-01-12 Qualcomm Incorporated Context-based priors for object detection in images
US20170287137A1 (en) * 2016-03-31 2017-10-05 Adobe Systems Incorporated Utilizing deep learning for boundary-aware image segmentation
US20190130229A1 (en) * 2017-10-31 2019-05-02 Adobe Inc. Deep salient content neural networks for efficient digital object segmentation

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Publication number Publication date
GB2585971B (en) 2021-12-15
GB202004362D0 (en) 2020-05-13
GB202005704D0 (en) 2020-06-03
GB2586678A (en) 2021-03-03
GB202005714D0 (en) 2020-06-03
GB2586678B (en) 2022-06-22
GB2585971A (en) 2021-01-27
GB2585972A (en) 2021-01-27

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