Invention Grant
- Patent Title: Discovery of semantic similarities between images and text
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Application No.: US14839430Application Date: 2015-08-28
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Publication No.: US09836671B2Publication Date: 2017-12-05
- Inventor: Jianfeng Gao , Xiaodong He , Saurabh Gupta , Geoffrey G. Zweig , Forrest Iandola , Li Deng , Hao Fang , Margaret A. Mitchell , John C. Platt , Rupesh Kumar Srivastava
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06K9/52 ; G06K9/00 ; G06F17/27 ; G06N3/02 ; G06F17/30

Abstract:
Disclosed herein are technologies directed to discovering semantic similarities between images and text, which can include performing image search using a textual query, performing text search using an image as a query, and/or generating captions for images using a caption generator. A semantic similarity framework can include a caption generator and can be based on a deep multimodal similar model. The deep multimodal similarity model can receive sentences and determine the relevancy of the sentences based on similarity of text vectors generated for one or more sentences to an image vector generated for an image. The text vectors and the image vector can be mapped in a semantic space, and their relevance can be determined based at least in part on the mapping. The sentence associated with the text vector determined to be the most relevant can be output as a caption for the image.
Public/Granted literature
- US20170061250A1 DISCOVERY OF SEMANTIC SIMILARITIES BETWEEN IMAGES AND TEXT Public/Granted day:2017-03-02
Information query