Large pretrained (eg," foundation") models exhibit distinct capabilities depending on the
domain of data they are trained on. While these domains are generic, they may only barely …

Egocentric vision (aka first-person vision–FPV) applications have thrived over the past few
years, thanks to the availability of affordable wearable cameras and large annotated …

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 exponential growth of technology has resulted in a profusion of advanced imaging
devices and eases internet accessibility, leading to an increase in the creation and use of …

Video summarization technologies aim to create a concise and complete synopsis by
selecting the most informative parts of the video content. Several approaches have been …

Searching long egocentric videos with natural language queries (NLQ) has compelling
applications in augmented reality and robotics, where a fluid index into everything that a …

One of the critical multimedia analysis problems in today's digital world is video
summarization (VS). Many VS methods have been suggested based on deep learning …

What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …

Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level
intensity changes in the form of" events". Due to their sensing mechanism, event cameras …

We introduce an approach for pre-training egocentric video models using large-scale third-
person video datasets. Learning from purely egocentric data is limited by low dataset scale …