Invention Grant
- Patent Title: Recurrent neural network architectures which provide text describing images
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Application No.: US15456348Application Date: 2017-03-10
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Publication No.: US10387776B2Publication Date: 2019-08-20
- Inventor: Zhe Lin , Yufei Wang , Scott Cohen , Xiaohui Shen
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Brake Hughes Bellermann LLP
- Main IPC: G06K9/46
- IPC: G06K9/46 ; G06N3/08 ; G06F16/58 ; G06K9/62 ; G06N3/04 ; G06F17/27

Abstract:
Provided are systems and techniques that provide an output phrase describing an image. An example method includes creating, with a convolutional neural network, feature maps describing image features in locations in the image. The method also includes providing a skeletal phrase for the image by processing the feature maps with a first long short-term memory (LSTM) neural network trained based on a first set of ground truth phrases which exclude attribute words. Then, attribute words are provided by processing the skeletal phrase and the feature maps with a second LSTM neural network trained based on a second set of ground truth phrases including words for attributes. Then, the method combines the skeletal phrase and the attribute words to form the output phrase.
Public/Granted literature
- US20180260698A1 RECURRENT NEURAL NETWORK ARCHITECTURES WHICH PROVIDE TEXT DESCRIBING IMAGES Public/Granted day:2018-09-13
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