We present AssemblyHands, a large-scale benchmark dataset with accurate 3D hand pose
annotations, to facilitate the study of egocentric activities with challenging hand-object …

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 …

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 …

We present EgoHumans, a new multi-view multi-human video benchmark to advance the
state-of-the-art of egocentric human 3D pose estimation and tracking. Existing egocentric …

We propose a method for in-hand 3D scanning of an unknown object with a monocular
camera. Our method relies on a neural implicit surface representation that captures both the …

We present IMU2CLIP, a novel pre-training approach to align Inertial Measurement Unit
(IMU) motion sensor recordings with video and text, by projecting them into the joint …

Humans easily miss events in their surroundings due to limited short-term memory and field
of view. This happens, for example, while watching an instructor's machine repair …

The progression to “Pervasive Augmented Reality” envisions easy access to multimodal
information continuously. However, in many everyday scenarios, users are occupied …

Building an AI assistant that can seamlessly converse and instruct humans, in a user-centric
situated scenario, requires several essential abilities:(1) spatial and temporal understanding …

Project Aria pushes the frontiers of Egocentric AI with large-scale real-world data collection
using purposely designed glasses with privacy first approach. To protect the privacy of …