Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the data. Recorded signals include video, imu, accel, gyro, audio. Licence: Ego4D License Agreement (signed; licensor University of Bristol); purpose clause permits commercial or noncommercial product development for activity/object understanding, 3D reconstruction and VR/AR; no redistribution.
- Type
- Dataset
- Host
- Not reported
- DOI
- Not reported
- Licence
- Not reported
- Code & repos
- Access
- Not reported
- Subjects
- 931
- PPG sites
- None
- Setting
- Not reported
- Wrist
- Not reported
- Raw waveforms
- Not reported
- Papers
- Updated
- Nov 11, 2026

Key numbers
How it works
- Reference labels
- activity
Papers and models using this dataset· 5
Papers
AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the WildEvaluationarXiv preprint · 2026
COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity RecognitionProc. ACM IMWUT 10 · 2026
IMU2CLIP: Multimodal Contrastive Learning for IMU Motion Sensors from Egocentric Videos and TextarXiv preprint · 2022
Models
#44 of 158 most-used datasets by published papers and models · #22 of 70 IMU · #3 of 18 rPPG
Browse these 3 papers in the research explorer (filtered to Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the data)
Cite
No citation metadata yet.
Cite the ChatPPG record
Cite the dated snapshot 2026-10 for a fixed, reproducible version. Please also cite the original publications listed above.
APA
ChatPPG. (2026). Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the data: dataset record (Version 2026-10) [Data set]. ChatPPG Research Hub. https://chatppg.com/research/datasets/ego4d
BibTeX
@misc{chatppg_dataset_ego4d,
author = {{ChatPPG}},
title = {{Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the data: dataset record}},
year = {2026},
month = nov,
version = {2026-10},
howpublished = {\url{https://chatppg.com/research/datasets/ego4d}},
note = {ChatPPG Research Hub, Snapshot 2026-10, https://chatppg.com/research/snapshots/2026-10}
}CITATION.cff
cff-version: 1.2.0 message: "If you use this resource, please cite it as below." type: dataset title: "Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the data: dataset record" authors: - name: "ChatPPG" url: "https://chatppg.com/research/datasets/ego4d" repository-artifact: "https://chatppg.com/research/snapshots/2026-10" version: "2026-10" date-released: "2026-11-11"
History
Record updated
Papers
AnyMo: Geometry-Aware Setup-Agnostic Modeling of Human Motion in the WildUses Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the dataarXiv preprint · 2026
COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity RecognitionUses Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the dataProc. ACM IMWUT 10 · 2026
IMU2CLIP: Multimodal Contrastive Learning for IMU Motion Sensors from Egocentric Videos and TextUses Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the dataarXiv preprint · 2022
Models
AnyMoUses Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the dataFoundation modelIMU2026 · Open weights
IMU2CLIPUses Ego4D: 3,670 h of egocentric daily-life video from 931 camera wearers, with head-camera IMU on part of the dataFoundation modelIMU2022
