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    TEXT ADJUSTED VISUAL SEARCH
    2.
    发明申请
    TEXT ADJUSTED VISUAL SEARCH 有权

    公开(公告)号：US20220138247A1

    公开(公告)日：2022-05-05

    申请号：US17090150

    申请日：2020-11-05

    Applicant: ADOBE INC.

    Inventor： Mikhail Kotov ,  Roland Geisler ,  Saeid Motiian ,  Dylan Nathaniel Warnock ,  Michele Saad ,  Venkata Naveen Kumar Yadav Marri ,  Ajinkya Kale ,  Ryan Rozich ,  Baldo Faieta

    IPC: G06F16/532 ,  G06F16/583 ,  G06F16/538 ,  G06F16/2457

    Abstract: Embodiments of the technology described herein, provide improved visual search results by combining a visual similarity and a textual similarity between images. In an embodiment, the visual similarity is quantified as a visual similarity score and the textual similarity is quantified as a textual similarity score. The textual similarity is determined based on text, such as a title, associated with the image. The overall similarity of two images is quantified as a weighted combination of the textual similarity score and the visual similarity score. In an embodiment, the weighting between the textual similarity score and the visual similarity score is user configurable through a control on the search interface. In one embodiment, the aggregate similarity score is the sum of a weighted visual similarity score and a weighted textual similarity score.

    Concept disambiguation using multimodal embeddings
    3.
    发明授权
    Concept disambiguation using multimodal embeddings 有权

    公开(公告)号：US12249116B2

    公开(公告)日：2025-03-11

    申请号：US17656147

    申请日：2022-03-23

    Applicant: ADOBE INC.

    Inventor： Venkata Naveen Kumar Yadav Marri ,  Ajinkya Gorakhnath Kale

    IPC: G06V10/771 ,  G06N3/088 ,  G06V10/74 ,  G06V10/77 ,  G06V10/774 ,  G06V10/82

    Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure identify a plurality of candidate concepts in a knowledge graph (KG) that correspond to an image tag of an image; generate an image embedding of the image using a multi-modal encoder; generate a concept embedding for each of the plurality of candidate concepts using the multi-modal encoder; select a matching concept from the plurality of candidate concepts based on the image embedding and the concept embedding; and generate association data between the image and the matching concept.

    STYLE-BASED IMAGE GENERATION
    5.
    发明申请
    STYLE-BASED IMAGE GENERATION 有权

    公开(公告)号：US20250117973A1

    公开(公告)日：2025-04-10

    申请号：US18903151

    申请日：2024-10-01

    Applicant: ADOBE INC.

    Inventor： Fengbin Chen ,  Midhun Harikumar ,  Ajinkya Gorakhnath Kale ,  Hareesh Ravi ,  Venkata Naveen Kumar Yadav Marri

    IPC: G06T11/00

    Abstract: A method, apparatus, non-transitory computer readable medium, and system for media processing includes obtaining a text prompt and a style input, where the text prompt describes image content and the style input describes an image style, generating a text embedding based on the text prompt, where the text embedding represents the image content, generating a style embedding based on the style input, where the style embedding represents the image style, and generating a synthetic image based on the text embedding and the style embedding, where the text embedding is provided to the image generation model at a first step and the style embedding is provided to the image generation model at a second step after the first step.

    WEAK SUPERVISED TRAINING DATA FOR IMAGE TAGGING MODELS
    6.
    发明申请
    WEAK SUPERVISED TRAINING DATA FOR IMAGE TAGGING MODELS 有权

    公开(公告)号：US20240378863A1

    公开(公告)日：2024-11-14

    申请号：US18313642

    申请日：2023-05-08

    Applicant: ADOBE INC.

    Inventor： Venkata Naveen Kumar Yadav Marri ,  Ajinkya Gorakhnath Kale

    IPC: G06V10/774 ,  G06T9/00 ,  G06V20/70

    Abstract: Systems and methods for image tagging are provided. One aspect of the systems and methods includes encoding an image and a tag of the image using a multimodal encoder to obtain an image embedding and a text embedding, respectively. Another aspect of the systems and methods includes generating training data for a machine learning model by filtering a plurality of image-tag pairs based on a similarity between the image embedding and the text embedding. Another aspect of the systems and methods includes training the machine learning model using the training data.

    MULTILINGUAL TEXT-TO-IMAGE GENERATION
    10.
    发明公开
    MULTILINGUAL TEXT-TO-IMAGE GENERATION 审中-公开

    公开(公告)号：US20240338859A1

    公开(公告)日：2024-10-10

    申请号：US18296002

    申请日：2023-04-05

    Applicant: ADOBE INC.

    Inventor： Venkata Naveen Kumar Yadav Marri ,  Ajinkya Gorakhnath Kale

    IPC: G06T11/00 ,  G06F40/58 ,  G06V10/74 ,  G06V10/774 ,  G06V10/82

    CPC classification number: G06T11/00 ,  G06F40/58 ,  G06V10/74 ,  G06V10/774 ,  G06V10/82

    Abstract: Systems and methods for image processing are provided. One aspect of the systems and methods includes obtaining a text prompt in a first language. Another aspect of the systems and methods includes encoding the text prompt using a multilingual encoder to obtain a multilingual text embedding. Yet another aspect of the systems and methods includes processing the multilingual text embedding using a diffusion prior model to obtain an image embedding, wherein the diffusion prior model is trained to process multilingual text embeddings from the first language and a second language based on training data from the first language and the second language. Yet another aspect of the systems and methods includes generating an image using a diffusion model based on the image embedding, wherein the image includes an element corresponding to the text prompt.

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