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Computer Science > Computer Vision and Pattern Recognition

arXiv:2510.16134 (cs)
[Submitted on 17 Oct 2025 ]

Title: Aria Gen 2 Pilot Dataset

Title: Aria Gen 2 测试数据集

Authors:Chen Kong, James Fort, Aria Kang, Jonathan Wittmer, Simon Green, Tianwei Shen, Yipu Zhao, Cheng Peng, Gustavo Solaira, Andrew Berkovich, Nikhil Raina, Vijay Baiyya, Evgeniy Oleinik, Eric Huang, Fan Zhang, Julian Straub, Mark Schwesinger, Luis Pesqueira, Xiaqing Pan, Jakob Julian Engel, Carl Ren, Mingfei Yan, Richard Newcombe
Abstract: The Aria Gen 2 Pilot Dataset (A2PD) is an egocentric multimodal open dataset captured using the state-of-the-art Aria Gen 2 glasses. To facilitate timely access, A2PD is released incrementally with ongoing dataset enhancements. The initial release features Dia'ane, our primary subject, who records her daily activities alongside friends, each equipped with Aria Gen 2 glasses. It encompasses five primary scenarios: cleaning, cooking, eating, playing, and outdoor walking. In each of the scenarios, we provide comprehensive raw sensor data and output data from various machine perception algorithms. These data illustrate the device's ability to perceive the wearer, the surrounding environment, and interactions between the wearer and the environment, while maintaining robust performance across diverse users and conditions. The A2PD is publicly available at projectaria.com, with open-source tools and usage examples provided in Project Aria Tools.
Abstract: Aria Gen 2试点数据集(A2PD)是一个使用最先进的Aria Gen 2眼镜拍摄的以第一视角为中心的多模态开放数据集。 为了便于及时访问,A2PD会随着数据集的持续增强逐步发布。 初始版本包括Dia'ane,我们的主要参与者,她记录自己的日常活动,并与配备Aria Gen 2眼镜的朋友一起记录。 它涵盖了五个主要场景:清洁、烹饪、进食、玩耍和户外行走。 在每个场景中,我们提供全面的原始传感器数据以及各种机器感知算法的输出数据。 这些数据展示了设备感知佩戴者、周围环境以及佩戴者与环境之间交互的能力,同时在不同用户和条件下保持稳健的性能。 A2PD可在projectaria.com公开获取,Project Aria Tools中提供了开源工具和使用示例。
Subjects: Computer Vision and Pattern Recognition (cs.CV) ; Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Machine Learning (cs.LG); Robotics (cs.RO)
Cite as: arXiv:2510.16134 [cs.CV]
  (or arXiv:2510.16134v1 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2510.16134
arXiv-issued DOI via DataCite

Submission history

From: Chen Kong [view email]
[v1] Fri, 17 Oct 2025 18:21:11 UTC (972 KB)
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