title: Aria Everyday Activities Dataset
summary: We present Aria Everyday Activities (AEA) Dataset, an egocentric multimodal
  open dataset recorded using Project Aria glasses. AEA contains 143 daily
  activity sequences recorded by multiple wearers in five geographically diverse
  indoor locations. Each of the recording contains multimodal sensor data
  recorded through the Project Aria glasses. In addition, AEA provides machine
  perception data including high frequency globally aligned 3D trajectories,
  scene point cloud, per-frame 3D eye gaze vector and time aligned speech
  transcription. In this paper, we demonstrate a few exemplar research
  applications enabled by this dataset, including neural scene reconstruction and
  prompted segmentation. AEA is an open source dataset that can be downloaded
  from projectaria.com. We are also providing open-source implementations and
  examples of how to use the dataset in Project Aria Tools.
paper_authors._id: 65d6bae46a36b5b354daeda7
paper_authors.name: Zhaoyang Lv
paper_authors._id: 65d6bae46a36b5b354daeda8
paper_authors.name: Nickolas Charron
paper_authors._id: 65d6bae46a36b5b354daeda9
paper_authors.name: Pierre Moulon
paper_authors._id: 65d6bae46a36b5b354daedaa
paper_authors.name: Alexander Gamino
paper_authors._id: 65d6bae46a36b5b354daedab
paper_authors.name: Cheng Peng
paper_authors._id: 65d6bae46a36b5b354daedac
paper_authors.name: Chris Sweeney
paper_authors._id: 65d6bae46a36b5b354daedad
paper_authors.name: Edward Miller
paper_authors._id: 65d6bae46a36b5b354daedae
paper_authors.name: Huixuan Tang
paper_authors._id: 65d6bae46a36b5b354daedaf
paper_authors.name: Jeff Meissner
paper_authors._id: 65d6bae46a36b5b354daedb0
paper_authors.name: Jing Dong
paper_authors._id: 65d6bae46a36b5b354daedb1
paper_authors.name: Kiran Somasundaram
paper_authors._id: 65d6bae46a36b5b354daedb2
paper_authors.name: Luis Pesqueira
paper_authors._id: 65d6bae46a36b5b354daedb3
paper_authors.name: Mark Schwesinger
paper_authors._id: 65d6bae46a36b5b354daedb4
paper_authors.name: Omkar Parkhi
paper_authors._id: 65d6bae46a36b5b354daedb5
paper_authors.name: Qiao Gu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-09-22T12:49:13.248Z
paper_authors._id: 63d1df92f7f31a66a2d7292c
paper_authors.avatarUrl: /avatars/eb3339c1f2c82742b518b8a7f142e99a.svg
paper_authors.fullname: Qiao Gu
paper_authors.type: user
paper_authors.user: guqiao
paper_authors._id: 65d6bae46a36b5b354daedb6
paper_authors.name: Renzo De Nardi
paper_authors._id: 65d6bae46a36b5b354daedb7
paper_authors.name: Shangyi Cheng
paper_authors._id: 65d6bae46a36b5b354daedb8
paper_authors.name: Steve Saarinen
paper_authors._id: 65d6bae46a36b5b354daedb9
paper_authors.name: Vijay Baiyya
paper_authors._id: 65d6bae46a36b5b354daedba
paper_authors.name: Yuyang Zou
paper_authors._id: 65d6bae46a36b5b354daedbb
paper_authors.name: Richard Newcombe
paper_authors._id: 65d6bae46a36b5b354daedbc
paper_authors.name: Jakob Julian Engel
paper_authors._id: 65d6bae46a36b5b354daedbd
paper_authors.name: Xiaqing Pan
paper_authors._id: 65d6bae46a36b5b354daedbe
paper_authors.name: Carl Ren
paper_title: Aria Everyday Activities Dataset
paper_summary: We present Aria Everyday Activities (AEA) Dataset, an egocentric multimodal
  open dataset recorded using Project Aria glasses. AEA contains 143 daily
  activity sequences recorded by multiple wearers in five geographically diverse
  indoor locations. Each of the recording contains multimodal sensor data
  recorded through the Project Aria glasses. In addition, AEA provides machine
  perception data including high frequency globally aligned 3D trajectories,
  scene point cloud, per-frame 3D eye gaze vector and time aligned speech
  transcription. In this paper, we demonstrate a few exemplar research
  applications enabled by this dataset, including neural scene reconstruction and
  prompted segmentation. AEA is an open source dataset that can be downloaded
  from projectaria.com. We are also providing open-source implementations and
  examples of how to use the dataset in Project Aria Tools.
paper_ai_keywords: neural scene reconstruction prompted segmentation 3D trajectories scene point cloud 3D eye gaze vector machine perception time aligned speech transcription egocentric multimodal open dataset