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    IMAGE CROPPING USING PRE-GENERATED METADATA
    3.
    发明申请
    IMAGE CROPPING USING PRE-GENERATED METADATA 有权

    公开(公告)号：US20210407100A1

    公开(公告)日：2021-12-30

    申请号：US16912366

    申请日：2020-06-25

    Applicant: Amazon Technologies, Inc.

    Inventor： Sabine Sternig ,  Luitpold Staudigl ,  Pablo Barbachano ,  Thomas Sydney Austin Wallis ,  Muhammad Bilal Javed ,  Michael Donoser

    IPC: G06T7/168

    Abstract: In operating an ecommerce marketplace, pre-generated metadata is used to transform images after a request is received, in real-time, and with low latency. To accomplish the high-speed image transformation, an offline annotation of relevant image features is obtained using machine learning and metadata is stored based upon the results. The metadata is then used to perform the high-speed image transformation at request time. The transformations can include image cropping, adjustment in saturation, contrast, brightness, extracting portions of the image, etc. In one example, the metadata includes a bounding box giving coordinates of how to crop an image so that the image can be cropped without analyzing content or context of the image. Instead, to obtain the coordinates of the bounding box, content and context of the image are analyzed in pre-request processing. In this way, when the request is received, the more difficult and time-consuming processing is already completed.

    Attribute-based content selection and search
    4.
    发明授权
    Attribute-based content selection and search 有权

    公开(公告)号：US11829445B1

    公开(公告)日：2023-11-28

    申请号：US17361905

    申请日：2021-06-29

    Applicant: Amazon Technologies, Inc.

    Inventor： Loris Bazzani ,  Michael Donoser ,  Yuxin Hou ,  Eleonora Vig

    IPC: G06F18/22 ,  G06F16/532 ,  G06F3/0482 ,  G06N3/08 ,  G06N3/04

    CPC classification number: G06F18/22 ,  G06F16/532 ,  G06F3/0482 ,  G06N3/04 ,  G06N3/08

    Abstract: Systems and techniques are generally described for attribute-based content selection and search. In some examples, a graphical user interface (GUI) may display an image of a first product comprising a plurality of visual attributes. In some further examples, the GUI may display at least a first control button with data identifying a first visual attribute of the plurality of visual attributes. In some cases, a first selection of the first control button may be received. In some examples, a first plurality of products may be determined based at least in part on the first selection of the first control button. The first plurality of products may be determined based on a visual similarity to the first product, and a visual dissimilarity to the first product with respect to the first visual attribute. In some examples, the first plurality of products may be displayed on the GUI.

    Feature based image detection
    5.
    发明授权
    Feature based image detection 有权

    公开(公告)号：US11341660B1

    公开(公告)日：2022-05-24

    申请号：US16834958

    申请日：2020-03-30

    Applicant: Amazon Technologies, Inc.

    Inventor： Nikhil Garg ,  Brad Bowman ,  Toma Belenzada ,  Michael Donoser

    IPC: G06T7/33 ,  G06Q30/06 ,  G06V10/10

    Abstract: System and methods are provided for improved visual search systems that can use local features of images. The search system provides a user interface that enables a user to select areas or portions of an image to search on the selected features and the overall appearance of the image. The search system further provides customized user interfaces to exclude certain portions of images from the search algorithms. The search system can be used to detect potential intellectual property risks associated with items in an electronic catalog.

    SEARCH RESULT IMAGE SELECTION TECHNIQUES
    6.
    发明申请
    SEARCH RESULT IMAGE SELECTION TECHNIQUES 审中-公开

    公开(公告)号：US20200233898A1

    公开(公告)日：2020-07-23

    申请号：US16254032

    申请日：2019-01-22

    Applicant: Amazon Technologies, Inc.

    Inventor： Zohar Barzelay ,  Brad Bowman ,  Michael Donoser ,  Nikhil Garg ,  Matthieu Guillaumin

    IPC: G06F16/538 ,  G06F16/2457 ,  G06F16/54 ,  G06F16/9535 ,  G06Q30/06 ,  G06N3/08

    Abstract: Techniques for prioritizing images associated with an item to display an appropriate image based on a query are described herein. For example, an attention score for an item attribute in an image of an item may be generated based at least in part on a model that uses one or more images of the item. The item attribute for the item associated with a query may be obtained. A plurality of items may be determined based at least in part on the item attribute being associated with the plurality of items where an individual item of the plurality of items includes a plurality of images of the item. The plurality of images of the individual item may be ranked based at least in part on corresponding attention scores associated with each image of the plurality of images.

    Relevant text identification based on image feature selection
    7.
    发明授权
    Relevant text identification based on image feature selection 有权

    公开(公告)号：US11521018B1

    公开(公告)日：2022-12-06

    申请号：US16162007

    申请日：2018-10-16

    Applicant: Amazon Technologies, Inc.

    Inventor： Zohar Barzelay ,  Michael Donoser

    IPC: G06K9/62 ,  G06F3/04812 ,  G06F3/0484 ,  G06V10/20 ,  G06V30/10

    Abstract: Techniques are generally described for predicting text relevant to image data. In various examples, the techniques may include receiving image data comprising a first portion. The first portion of the image data may correspond to a first plurality of pixels when rendered on the display. Text data comprising a first text related to the first portion of the image data may be received. A first vector representation of the first portion of the image data may be determined. In some examples, a correspondence between the first portion of the image data and the first text may be determined based at least in part on the first vector representation. A first identifier of the first portion of image data may be stored in a data structure in association with a second identifier of the first text.

    Image cropping using pre-generated metadata
    8.
    发明授权
    Image cropping using pre-generated metadata 有权

    公开(公告)号：US11361447B2

    公开(公告)日：2022-06-14

    申请号：US16912366

    申请日：2020-06-25

    Applicant: Amazon Technologies, Inc.

    Inventor： Sabine Sternig ,  Luitpold Staudigl ,  Pablo Barbachano ,  Thomas Sydney Austin Wallis ,  Muhammad Bilal Javed ,  Michael Donoser

    IPC: G06F16/583 ,  G06T7/168 ,  G06V10/46 ,  G06V40/16

    Abstract: In operating an ecommerce marketplace, pre-generated metadata is used to transform images after a request is received, in real-time, and with low latency. To accomplish the high-speed image transformation, an offline annotation of relevant image features is obtained using machine learning and metadata is stored based upon the results. The metadata is then used to perform the high-speed image transformation at request time. The transformations can include image cropping, adjustment in saturation, contrast, brightness, extracting portions of the image, etc. In one example, the metadata includes a bounding box giving coordinates of how to crop an image so that the image can be cropped without analyzing content or context of the image. Instead, to obtain the coordinates of the bounding box, content and context of the image are analyzed in pre-request processing. In this way, when the request is received, the more difficult and time-consuming processing is already completed.

    Search result image selection techniques
    9.
    发明授权
    Search result image selection techniques 有权

    公开(公告)号：US11176191B2

    公开(公告)日：2021-11-16

    申请号：US16254032

    申请日：2019-01-22

    Applicant: Amazon Technologies, Inc.

    Inventor： Zohar Barzelay ,  Brad Bowman ,  Michael Donoser ,  Nikhil Garg ,  Matthieu Guillaumin

    IPC: G06F16/53 ,  G06F16/538 ,  G06F16/54 ,  G06F16/9535 ,  G06F16/2457 ,  G06N3/08 ,  G06Q30/06 ,  G06F3/0485

    Abstract: Techniques for prioritizing images associated with an item to display an appropriate image based on a query are described herein. For example, an attention score for an item attribute in an image of an item may be generated based at least in part on a model that uses one or more images of the item. The item attribute for the item associated with a query may be obtained. A plurality of items may be determined based at least in part on the item attribute being associated with the plurality of items where an individual item of the plurality of items includes a plurality of images of the item. The plurality of images of the individual item may be ranked based at least in part on corresponding attention scores associated with each image of the plurality of images.

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