Image Retrieval with Deep Local Feature Descriptors and Attention-Based Keypoint Descriptors

    公开(公告)号:US20200004777A1

    公开(公告)日:2020-01-02

    申请号:US16558852

    申请日:2019-09-03

    Applicant: Google LLC

    Abstract: Systems and methods of the present disclosure can use machine-learned image descriptor models for image retrieval applications and other applications. A trained image descriptor model can be used to analyze a plurality of database images to create a large-scale index of keypoint descriptors associated with the database images. An image retrieval application can provide a query image as input to the trained image descriptor model, resulting in receipt of a set of keypoint descriptors associated with the query image. Keypoint descriptors associated with the query image can be analyzed relative to the index to determine matching descriptors (e.g., by implementing a nearest neighbor search). Matching descriptors can then be geometrically verified and used to identify one or more matching images from the plurality of database images to retrieve and provide as output (e.g., by providing for display) within the image retrieval application.

    Image retrieval with deep local feature descriptors and attention-based keypoint descriptors

    公开(公告)号:US10650042B2

    公开(公告)日:2020-05-12

    申请号:US16558852

    申请日:2019-09-03

    Applicant: Google LLC

    Abstract: Systems and methods of the present disclosure can use machine-learned image descriptor models for image retrieval applications and other applications. A trained image descriptor model can be used to analyze a plurality of database images to create a large-scale index of keypoint descriptors associated with the database images. An image retrieval application can provide a query image as input to the trained image descriptor model, resulting in receipt of a set of keypoint descriptors associated with the query image. Keypoint descriptors associated with the query image can be analyzed relative to the index to determine matching descriptors (e.g., by implementing a nearest neighbor search). Matching descriptors can then be geometrically verified and used to identify one or more matching images from the plurality of database images to retrieve and provide as output (e.g., by providing for display) within the image retrieval application.

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