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公开(公告)号：US09811765B2
公开(公告)日：2017-11-07
申请号：US14995032
申请日：2016-01-13
Applicant: Adobe Systems Incorporated
Inventor： Zhaowen Wang , Quanzeng You , Hailin Jin , Chen Fang
CPC classification number: G06K9/6269 , G06F17/30247 , G06F17/3028 , G06F17/30675 , G06K9/00664 , G06K9/4604 , G06K9/4628 , G06K9/6202 , G06K9/6274 , G06N3/0445 , G06N3/08 , G06N7/005
Abstract: Techniques for image captioning with weak supervision are described herein. In implementations, weak supervision data regarding a target image is obtained and utilized to provide detail information that supplements global image concepts derived for image captioning. Weak supervision data refers to noisy data that is not closely curated and may include errors. Given a target image, weak supervision data for visually similar images may be collected from sources of weakly annotated images, such as online social networks. Generally, images posted online include “weak” annotations in the form of tags, titles, labels, and short descriptions added by users. Weak supervision data for the target image is generated by extracting keywords for visually similar images discovered in the different sources. The keywords included in the weak supervision data are then employed to modulate weights applied for probabilistic classifications during image captioning analysis.
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公开(公告)号：US09792534B2
公开(公告)日：2017-10-17
申请号：US14995042
申请日：2016-01-13
Applicant: Adobe Systems Incorporated
Inventor： Zhaowen Wang , Quanzeng You , Hailin Jin , Chen Fang
CPC classification number: G06K9/6269 , G06F17/30253 , G06F17/3028 , G06K9/00664 , G06K9/4604 , G06K9/4628 , G06K9/6202 , G06K9/6274 , G06N3/08
Abstract: Techniques for image captioning with word vector representations are described. In implementations, instead of outputting results of caption analysis directly, the framework is adapted to output points in a semantic word vector space. These word vector representations reflect distance values in the context of the semantic word vector space. In this approach, words are mapped into a vector space and the results of caption analysis are expressed as points in the vector space that capture semantics between words. In the vector space, similar concepts with have small distance values. The word vectors are not tied to particular words or a single dictionary. A post-processing step is employed to map the points to words and convert the word vector representations to captions. Accordingly, conversion is delayed to a later stage in the process.
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公开(公告)号：US20170200065A1
公开(公告)日：2017-07-13
申请号：US14995032
申请日：2016-01-13
Applicant: Adobe Systems Incorporated
Inventor： Zhaowen Wang , Quanzeng You , Hailin Jin , Chen Fang
CPC classification number: G06K9/6269 , G06F17/30247 , G06F17/3028 , G06F17/30675 , G06K9/00664 , G06K9/4604 , G06K9/4628 , G06K9/6202 , G06K9/6274 , G06N3/0445 , G06N3/08 , G06N7/005
Abstract: Techniques for image captioning with weak supervision are described herein. In implementations, weak supervision data regarding a target image is obtained and utilized to provide detail information that supplements global image concepts derived for image captioning. Weak supervision data refers to noisy data that is not closely curated and may include errors. Given a target image, weak supervision data for visually similar images may be collected from sources of weakly annotated images, such as online social networks. Generally, images posted online include “weak” annotations in the form of tags, titles, labels, and short descriptions added by users. Weak supervision data for the target image is generated by extracting keywords for visually similar images discovered in the different sources. The keywords included in the weak supervision data are then employed to modulate weights applied for probabilistic classifications during image captioning analysis.
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公开(公告)号：US20170200066A1
公开(公告)日：2017-07-13
申请号：US14995042
申请日：2016-01-13
Applicant: Adobe Systems Incorporated
Inventor： Zhaowen Wang , Quanzeng You , Hailin Jin , Chen Fang
CPC classification number: G06K9/6269 , G06F17/30253 , G06F17/3028 , G06K9/00664 , G06K9/4604 , G06K9/4628 , G06K9/6202 , G06K9/6274 , G06N3/08
Abstract: Techniques for image captioning with word vector representations are described. In implementations, instead of outputting results of caption analysis directly, the framework is adapted to output points in a semantic word vector space. These word vector representations reflect distance values in the context of the semantic word vector space. In this approach, words are mapped into a vector space and the results of caption analysis are expressed as points in the vector space that capture semantics between words. In the vector space, similar concepts with have small distance values. The word vectors are not tied to particular words or a single dictionary. A post-processing step is employed to map the points to words and convert the word vector representations to captions. Accordingly, conversion is delayed to a later stage in the process.
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