The exponential growth in the production of video contents in different industries causes an
urgent need for effective video summarization (VS) techniques, in order to get an optimal …

With ever-increasing dataset sizes, subset selection techniques are becoming increasingly
important for a plethora of tasks. It is often necessary to guide the subset selection to achieve …

With the massive expansion of videos on the internet, searching through millions of them
has become quite challenging. Smartphones, recording devices, and file sharing are all …

Video highlight detection is a task to automatically select the most engaging moments from a
long video. This problem is highly challenging since it aims to learn a general way of finding …

Information-theoretic quantities like entropy and mutual information have found numerous
uses in machine learning. It is well known that there is a strong connection between these …

Submodular functions are a special class of set functions which naturally model the notion of
representativeness, diversity, coverage etc. and have been shown to be computationally …

The key events extraction from a video for the best representation of its contents is known as
video summarization. In this study, the game of cricket is specifically considered for …

Few-shot classification (FSC) requires training models using a few (typically one to five) data
points per class. Meta-learning has proven to be able to learn a parametrized model for FSC …

Automatic video summarization is still an unsolved problem due to several challenges. We
take steps towards making it more realistic by addressing the following challenges. Firstly …

Automatic video summarization is still an unsolved problem due to several challenges. The
currently available datasets either have very short videos or have few long videos of only a …