6-2 支持用户反馈的对话式图像检索.pdf

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1、01Background02Unstructured Feedback03Structured Feedback04Future Work目录 CONTENT|01BackgroundBackgroundHuge economic value of fashion domain.|BackgroundNumerous online clothing data on the Internet.Precise image retrieval that meets the users search intent is a key challenge.|BackgroundConventional p

2、aradigms for item search take either text or image as theinput query to search for items of interest.a blue overcoat with a lapel collar and a belt around the waist Text QueryImage QueryUnstructured feedback+I want the dress to be black and more professional.|Background Flexible image retrieval:allo

3、w users to use reference image and modification feedbackto search items.Structured feedback|Background Application:dialog-based fashion search/conversational fashion search At the beginning,the recommended fashionproduct image may not be the desired one.Based on this reference image,the usertypicall

4、y would like to refine the retrieval byproviding feedbacks,describing the relativedifference between the current retrievedreference image and his/her desired one.|02Structured FeedbackTask A query image can be described by itsassociated attributes:=a1,1,2,The target image can be described by:=a1,1,2

5、,Attribute Manipulation1and 2are the to-be-manipulated attributes.|Related WorkCategoryRelated WorkFeature Fusion-basedMemory-Augmented Attribute Manipulation Networks for Interactive FashionSearch,In CVPR2017.Feature Substitution-basedEfficient Multi-Attribute Similarity Learning Towards Attribute-

6、based FashionSearch,In WACV2018.Automatic Spatially-aware Fashion Concept Discovery,In ICCV2017.Learning Attribute Representations with Localization for Flexible FashionSearch,In CVPR2018.|Fusion-based Method Memory-AugmentedAttributeManipulationNetworksforInteractiveFashion Search.In CVPR2017.Attri