There has been an exponential growth in the amount of visual data on a daily basis
acquired from single or multi-view surveillance camera networks. This massive amount of …

Video summarization is a challenging problem in part because knowing which part of a
video is important requires prior knowledge about its main topic. We present TVSum, an …

Video summarization is a challenging problem with great application potential. Whereas
prior approaches, largely unsupervised in nature, focus on sampling useful frames and …

Video summarization has unprecedented importance to help us digest, browse, and search
today's ever-growing video collections. We propose a novel subset selection technique that …

We present video co-summarization, a novel perspective to video summarization that
exploits visual co-occurrence across multiple videos. Motivated by the observation that …

Video summarization is a challenging under-constrained problem because the underlying
summary of a single video strongly depends on users' subjective understandings. Data …

Most of the prior works summarize videos by either exploring different heuristically designed
criteria in an unsupervised way or develo** fully supervised algorithms by leveraging …

How to manage, store, and index large numbers of videos is an urgent problem to be solved.
Although there are many video summarization models achieving good results, models …

We present a method that is able to find the most informative video portions, leading to a
summarization of video sequences. In contrast to the existing works, our method is able to …

Large collections of videos are grouped into clusters by a topic keyword, such as" Eiffel
Tower" or" Surfing", with many important visual concepts repeating across them. Such a …