Find and Focus: Retrieve and Localize Video Events with Natural Language Queries
文献类型：会议论文
| 作者 | Dian Shao; Yu Xiong; Yue Zhao; Qingqiu Huang; Yu Qiao; Dahua Lin |
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 英文摘要 | The thriving of video sharing services brings new challenges to video retrieval, e.g. the rapid growth in video duration and content diversity. Meeting such challenges calls for new techniques that can effectively retrieve videos with natural language queries. Existing methods along this line, which mostly rely on embedding videos as a whole, remain far from satisfactory for real-world applications due to the limited expressive power. In this work, we aim to move beyond this limitation by delving into the internal structures of both sides, the queries and the videos. Specifically, we propose a new framework called Find and Focus (FIFO), which not only performs top-level matching (paragraph vs. video), but also makes part-level associations, localizing a video clip for each sentence in the query with the help of a focusing guide. These levels are complementary – the top-level matching narrows the search while the part-level localization refines the results. On both ActivityNet Captions and modified LSMDC datasets, the proposed framework achieves remarkable performance gains. |
| URL标识 | 查看原文 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/13691]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 推荐引用方式 GB/T 7714 | Dian Shao,Yu Xiong,Yue Zhao,et al. Find and Focus: Retrieve and Localize Video Events with Natural Language Queries[C]. 见:. 2018. |
入库方式： OAI收割
来源：深圳先进技术研究院
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