知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

19 records (took 0.012 seconds)

    Custom auto tagging of multiple objects
    11.
    发明授权
    Custom auto tagging of multiple objects 有权

    公开(公告)号：US10853700B2

    公开(公告)日：2020-12-01

    申请号：US16928949

    申请日：2020-07-14

    Applicant: Adobe Inc.

    Inventor： Jayant Kumar ,  Zhe Lin ,  Vipulkumar C. Dalal

    IPC: G06K9/62

    Abstract: There is described a computing device and method in a digital medium environment for custom auto tagging of multiple objects. The computing device includes an object detection network and multiple image classification networks. An image is received at the object detection network and includes multiple visual objects. First feature maps are applied to the image at the object detection network and generate object regions associated with the visual objects. The object regions are assigned to the multiple image classification networks, and each image classification network is assigned to a particular object region. The second feature maps are applied to each object region at each image classification network, and each image classification network outputs one or more classes associated with a visual object corresponding to each object region.

    MULTI-OBJECT IMAGE PARSING USING NEURAL NETWORK PIPELINE
    16.
    发明申请
    MULTI-OBJECT IMAGE PARSING USING NEURAL NETWORK PIPELINE 有权

    公开(公告)号：US20210248748A1

    公开(公告)日：2021-08-12

    申请号：US16789088

    申请日：2020-02-12

    Applicant: Adobe Inc.

    Inventor： Kerem Can Turgutlu ,  Jayant Kumar ,  Jianming Zhang ,  Zhe Lin

    IPC: G06T7/11 ,  G06T3/40 ,  G06T7/194 ,  G06N3/04

    Abstract: Techniques are disclosed for parsing a source image, to identify segments of one or more objects within the source image. The parsing is carried out by an image parsing pipeline that includes three distinct stages comprising three respectively neural network models. The source image can include one or more objects. A first neural network model of the pipeline identifies a section of the source image that includes the object comprising a plurality of segments. A second neural network model of the pipeline generates, from the section of the source image, a mask image, where the mask image identifys one or more segments of the object. A third neural network model of the pipeline further refines the identification of the segments in the mask image, to generate a parsed image. The parsed image identifies the segments of the object, by assigning corresponding unique labels to pixels of different segments of the object.

    Custom Auto Tagging of Multiple Objects
    17.
    发明授权
    Custom Auto Tagging of Multiple Objects 有权

    公开(公告)号：US10733480B2

    公开(公告)日：2020-08-04

    申请号：US16039311

    申请日：2018-07-18

    Applicant: Adobe Inc.

    Inventor： Jayant Kumar ,  Zhe Lin ,  Vipulkumar C. Dalal

    IPC: G06K9/62

    Abstract: There is described a computing device and method in a digital medium environment for custom auto tagging of multiple objects. The computing device includes an object detection network and multiple image classification networks. An image is received at the object detection network and includes multiple visual objects. First feature maps are applied to the image at the object detection network and generate object regions associated with the visual objects. The object regions are assigned to the multiple image classification networks, and each image classification network is assigned to a particular object region. The second feature maps are applied to each object region at each image classification network, and each image classification network outputs one or more classes associated with a visual object corresponding to each object region.

    Multimodal input contextual font recommendations
    18.
    发明授权
    Multimodal input contextual font recommendations 有权

    公开(公告)号：US11775734B2

    公开(公告)日：2023-10-03

    申请号：US17534937

    申请日：2021-11-24

    Applicant: Adobe Inc.

    Inventor： Sanat Sharma ,  Jing Zheng ,  Jayant Kumar

    IPC: G06F40/109 ,  G06N3/02 ,  G06N5/02

    CPC classification number: G06F40/109 ,  G06N3/02 ,  G06N5/02

    Abstract: Embodiments are disclosed for receiving a modal input including at least one of a text input or an image input. The method may include extracting an intent label from the modal input. The method may further include generating, by an intent embedding generator, an intent embedding from the intent label. The method may further include comparing the intent embedding to a plurality of candidate font embeddings to obtain one or more candidate fonts based on a similarity of the intent embedding to the plurality of candidate font embeddings in an embedding space. The method may further include identifying a recommended font based on the similarity of the intent embedding to a selected candidate font embedding of the plurality of candidate font embeddings.

Patent Agency Ranking