论文标题
使用自然语言查询搜索原始视频数据库
Searching a Raw Video Database using Natural Language Queries
论文作者
论文摘要
随着时间的流逝，正在制作和存储在视频流平台数据库中的视频数量一直在呈指数增长。这个庞大的数据库应该很容易索引，以找到必要的剪辑或视频以匹配给定的搜索规范，最好以文本查询的形式匹配。这项工作旨在提供端到端管道，以搜索最终用户的语音查询的视频数据库。该管道利用复发性神经网络与卷积神经网络结合使用，以生成数据库中存在的视频片段的标题。
The number of videos being produced and consequently stored in databases for video streaming platforms has been increasing exponentially over time. This vast database should be easily index-able to find the requisite clip or video to match the given search specification, preferably in the form of a textual query. This work aims to provide an end-to-end pipeline to search a video database with a voice query from the end user. The pipeline makes use of Recurrent Neural Networks in combination with Convolutional Neural Networks to generate captions of the video clips present in the database.
