Visual Entity Linking

被引:0
|
作者
Tilak, Neha [1 ]
Gandhi, Sunil [1 ]
Oates, Tim
机构
[1] UMBC, Dept Comp Sci & Engn, Baltimore, MD 21250 USA
关键词
KNOWLEDGE; NETWORKS; WEB;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Entity linking is the task of identifying entities like people and places in textual data and linking them to corresponding entities in a knowledge base. In this paper we solve a visual equivalent of this task called visual entity linking. The goal is to link regions of images to corresponding entities in knowledge bases. Visual entity linking will enable computers to better understand visual content and thus can be used in tasks like image retrieval and visual question answering. More specifically, we propose a novel approach for linking image regions to entities in Dbpedia and Freebase. First, we select candidate entities using an automatic image description generation algorithm. We then extract image regions using object detection methods and compare them to depictions of entities in a knowledge base. We evaluate our approach on the Flickr8k dataset through surveys on Amazon Mechanical Turk, and present an extensive analysis to identify the sources of errors in our system.
引用
收藏
页码:665 / 672
页数:8
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