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VIRET at Video Browser Showdown 2020

机译:VIRET在2020年视频浏览器对决中

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摘要

During the last three years, the most successful systems at the Video Browser Showdown employed effective retrieval models where raw video data are automatically preprocessed in advance to extract semantic or low-level features of selected frames or shots. This enables users to express their search intents in the form of keywords, sketch, query example, or their combination. In this paper, we present new extensions to our interactive video retrieval system VIRET that won Video Browser Showdown in 2018 and achieved the second place at Video Browser Showdown 2019 and Lifelog Search Challenge 2019. The new features of the system focus both on updates of retrieval models and interface modifications to help users with query specification by means of informative visualizations.
机译:在最近三年中,视频浏览器对决中最成功的系统采用了有效的检索模型,该模型可以自动对原始视频数据进行预先预处理,以提取所选帧或镜头的语义或低级特征。这使用户能够以关键字,草图,查询示例或它们的组合的形式表达他们的搜索意图。在本文中,我们介绍了交互式视频检索系统VIRET的新扩展,该系统在2018年赢得了Video Browser Showdown并在Video Browser Showdown 2019和Lifelog Search Challenge 2019中获得了第二名。该系统的新功能都集中在检索的更新上模型和界面修改,以通过信息可视化帮助用户确定查询规范。

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