IR Questioner: QA-based Interactive Retrieval System
IR Questioner: QA-based Interactive Retrieval System
复制标题
DOI：
10.1145/3460426.3463577
复制
发表时间：
2021-08
期刊：
影响因子：
--
通讯作者：
Rintaro Yanagi;Ren Togo;Takahiro Ogawa;M. Haseyama
中科院分区：
文献类型：
--
作者：
Rintaro Yanagi;Ren Togo;Takahiro Ogawa;M. Haseyama
从给定的文本查询中检索图像（文本到图像检索）是最基本的系统之一，它被有效地用于Web上的数据库（DB）。为了使它们更加通用和熟悉，应该考虑一个自适应的检索系统，即使是个人数据库，如智能手机和生活记录设备中的图像。在本文中，我们提出了一种新的文本到图像检索系统，是专门为个人数据库。与跨模态计划和问答计划，开发的系统使用户能够获得所需的图像有效地甚至从个人数据库。我们的演示可在https://sites.google.com/view/ir-questioner/上获得。
Image retrieval from a given text query (text-to-image retrieval) is one of the most essential systems, and it is effectively utilized for databases (DBs) on the Web. To make them more versatile and familiar, a retrieval system that is adaptive even for personal DBs such as images in smartphones and lifelogging devices should be considered. In this paper, we present a novel text-to-image retrieval system that is specialized for personal DBs. With the cross-modal scheme and the question-answering scheme, the developed system enables users to obtain the desired image effectively even from personal DBs. Our demo is available at https://sites.google.com/view/ir-questioner/.