Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …

In this paper we tackle the problem of self-supervised video alignment and activity progress
prediction using in-the-wild videos. Our proposed self-supervised representation learning …

We investigate exocentric-to-egocentric cross-view translation, which aims to generate a first-
person (egocentric) view of an actor based on a video recording that captures the actor from …

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 …

Understanding human actions from videos of first-person view poses significant challenges.
Most prior approaches explore representation learning on egocentric videos only while …

Real-life applications of action recognition often require a fine-grained understanding of
subtle movements, eg, in sports analytics, user interactions in AR/VR, and surgical videos …

We consider the problem of transferring a temporal action segmentation system initially
designed for exocentric (fixed) cameras to an egocentric scenario, where wearable cameras …

Egocentric videos provide comprehensive contexts for user and scene understanding,
spanning multisensory perception to behavioral interaction. We propose Spherical World …

Being able to map the activities of others into one's own point of view is one fundamental
human skill even from a very early age. Taking a step toward understanding this human …

As wearable cameras become more popular an important question emerges: how to identify
camera wearers within the perspective of conventional static cameras. The drastic difference …