V3C1 Dataset: An Evaluation of Content Characteristics.

ICMR '19: International Conference on Multimedia Retrieval Ottawa ON Canada June, 2019(2019)

引用 52|浏览46
暂无评分
摘要
In this work we analyze content statistics of the V3C1 dataset, which is the first partition of theVimeo Creative Commons Collection (V3C). The dataset has been designed to represent true web videos in the wild, with good visual quality and diverse content characteristics, and will serve as evaluation basis for the Video Browser Showdown 2019-2021 and TREC Video Retrieval (TRECVID) Ad-Hoc Video Search tasks 2019-2021. The dataset comes with a shot segmentation (around 1 million shots) for which we analyze content specifics and statistics. Our research shows that the content of V3C1 is very diverse, has no predominant characteristics and provides a low self-similarity. Thus it is very well suited for video retrieval evaluations as well as for participants of TRECVID AVS or the VBS.
更多
查看译文
关键词
V3C, video collection, video analytics, content statistics, TRECVID
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要