Visual lifelogging consists of acquiring images that capture the daily experiences of the user
by wearing a camera over a long period of time. The pictures taken offer considerable …

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …

The introduction of wearable video cameras (eg, GoPro) in the consumer market has
promoted video life-logging, motivating users to generate large amounts of video data. This …

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 …

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 …

Exploiting the inner-shot and inter-shot dependencies is essential for key-shot based video
summarization. Current approaches mainly devote to modeling the video as a frame …

Activity detection and classification are very important for autonomous monitoring of humans
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …

This paper proposes a novel approach and a new benchmark for video summarization.
Thereby we focus on user videos, which are raw videos containing a set of interesting …

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 …