期刊
出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3323873.3325034
关键词
known-item search; deep neural networks; video retrieval
资金
- Czech Science Foundation (GACR) project [19-22071Y]
Known-item search in large video collections still represents a challenging task for current video retrieval systems that have to rely both on state-of-the-art ranking models and interactive means of retrieval. We present a general overview of the current version of the VIRET tool, an interactive video retrieval system that successfully participated at several international evaluation campaigns. The system is based on multi-modal search and convenient inspection of results. Based on collected query logs of four users controlling instances of the tool at the Video Browser Showdown 2019, we highlight query modification statistics and a list of successful query formulation strategies. We conclude that the VIRET tool represents a competitive reference interactive system for effective known-item search in one thousand hours of video.
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