This paper addresses the problem of unsupervised video summarization, formulated as
selecting a sparse subset of video frames that optimally represent the input video. Our key …

A generic video summary is an abridged version of a video that conveys the whole story and
features the most important scenes. Yet the importance of scenes in a video is often …

We propose a novel supervised learning technique for summarizing videos by automatically
selecting keyframes or key subshots. Casting the task as a structured prediction problem …

This paper addresses the problem of video summarization. Given an input video, the goal is
to select a subset of the frames to create a summary video that optimally captures the …

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 propose a principled approach to summarization of visual data (images or video) based
on optimization of a well-defined similarity measure. The problem we consider is re-targeting …

We consider the problem of video summarization. Given an input raw video, the goal is to
select a small subset of key frames from the input video to create a shorter summary video …

In this paper, we address the problem of unsupervised video summarization that
automatically extracts key-shots from an input video. Specifically, we tackle two critical …

Supervised learning techniques have shown substantial progress on video summarization.
State-of-the-art approaches mostly regard the predicted summary and the human summary …

With the growing popularity of short-form video sharing platforms such as Instagram and
Vine, there has been an increasing need for techniques that automatically extract highlights …