Ego4D: Around the World in 3,000 Hours of Egocentric Video

dc.contributor.authorKristen Grauman
dc.contributor.authorAndrew Westbury
dc.contributor.authorEugene H. Byrne
dc.contributor.authorZachary Chavis
dc.contributor.authorAntonino Furnari
dc.contributor.authorRohit Girdhar
dc.contributor.authorJackson Hamburger
dc.contributor.authorHao Jiang
dc.contributor.authorMiao Liu
dc.contributor.authorXingyu Liu
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T13:50:20Z
dc.date.available2026-03-22T13:50:20Z
dc.date.issued2022
dc.descriptionCitaciones: 484
dc.description.abstractWe introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of dailylife 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. Project page: https://ego4d-data.org/
dc.identifier.doi10.1109/cvpr52688.2022.01842
dc.identifier.urihttps://doi.org/10.1109/cvpr52688.2022.01842
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/43015
dc.language.isoen
dc.relation.ispartof2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
dc.sourceThe University of Texas at Austin
dc.subjectSuite
dc.subjectComputer science
dc.subjectBenchmark (surveying)
dc.subjectGaze
dc.subjectEvent (particle physics)
dc.subjectPerception
dc.subjectIdentification (biology)
dc.subjectMultimedia
dc.subjectArtificial intelligence
dc.subjectHuman–computer interaction
dc.titleEgo4D: Around the World in 3,000 Hours of Egocentric Video
dc.typearticle

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