  We 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. Project page:
https://ego4d-data.org/
