Ego4D: Around the World in 3,600 Hours of Egocentric Video

dc.contributor.authorKristen Grauman
dc.contributor.authorAndrew Westbury
dc.contributor.authorEugene H. Byrne
dc.contributor.authorVincent Cartillier
dc.contributor.authorZachary Chavis
dc.contributor.authorAntonino Furnari
dc.contributor.authorRohit Girdhar
dc.contributor.authorJackson Hamburger
dc.contributor.authorHao Jiang
dc.contributor.authorDevansh Kukreja
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T14:23:16Z
dc.date.available2026-03-22T14:23:16Z
dc.date.issued2024
dc.descriptionCitaciones: 7
dc.description.abstractWe introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outdoor, workplace, leisure, etc.) captured by 931 unique camera wearers from 74 worldwide locations and 9 different countries. The approach to collection is designed to uphold rigorous privacy and ethics standards, with consenting participants and robust de-identification procedures where relevant. Ego4D dramatically expands the volume of diverse egocentric video footage publicly available to the research community. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event. Furthermore, we present a host of new benchmark challenges centered around understanding the first-person visual experience in the past (querying an episodic memory), present (analyzing hand-object manipulation, audio-visual conversation, and social interactions), and future (forecasting activities). By publicly sharing this massive annotated dataset and benchmark suite, we aim to push the frontier of first-person perception.
dc.identifier.doi10.1109/tpami.2024.3381075
dc.identifier.urihttps://doi.org/10.1109/tpami.2024.3381075
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/46216
dc.language.isoen
dc.publisherIEEE Computer Society
dc.relation.ispartofIEEE Transactions on Pattern Analysis and Machine Intelligence
dc.sourceMenlo School
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectComputer vision
dc.titleEgo4D: Around the World in 3,600 Hours of Egocentric Video
dc.typearticle

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