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

Abstract We introduce the Aria Digital Twin (ADT)-an egocentric dataset captured using Aria
glasses with extensive object, environment, and human level ground truth. This ADT release …

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 the visual world from the perspective of humans (egocentric) has been a
long-standing challenge in computer vision. Egocentric videos exhibit high scene complexity …

Egocentric sensors such as AR/VR devices capture human-object interactions and offer the
potential to provide task-assistance by recalling 3D locations of objects of interest in the …

Abstract 3D spatial understanding is highly valuable in the context of semantic modeling of
environments, agents, and their relationships. Semantic modeling approaches employed on …

Humans use multiple senses to comprehend the environment. Vision and language are two
of the most vital senses since they allow us to easily communicate our thoughts and …

The Associating Objects with Transformers (AOT) framework has exhibited exceptional
performance in a wide range of complex scenarios for video object tracking and …