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

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

13 Oct 2021CVPR 2022 1arXiv:2110.07058archive 2025-07-28

Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, Miguel Martin, Tushar Nagarajan, Ilija Radosavovic, Santhosh Kumar Ramakrishnan, Fiona Ryan, Jayant Sharma, Michael Wray, Mengmeng Xu, Eric Zhongcong Xu, Chen Zhao, Siddhant Bansal, Dhruv Batra, Vincent Cartillier, Sean Crane, Tien Do, Morrie Doulaty, Akshay Erapalli, Christoph Feichtenhofer, Adriano Fragomeni, Qichen Fu, Abrham Gebreselasie, Cristina Gonzalez, James Hillis, Xuhua Huang, Yifei HUANG, Wenqi Jia, Weslie Khoo, Jachym Kolar, Satwik Kottur, Anurag Kumar, Federico Landini, Chao Li, Yanghao Li, Zhenqiang Li, Karttikeya Mangalam, Raghava Modhugu, Jonathan Munro, Tullie Murrell, Takumi Nishiyasu, Will Price, Paola Ruiz Puentes, Merey Ramazanova, Leda Sari, Kiran Somasundaram, Audrey Southerland, Yusuke Sugano, Ruijie Tao, Minh Vo, Yuchen Wang, Xindi Wu, Takuma Yagi, Ziwei Zhao, Yunyi Zhu, Pablo Arbelaez, David Crandall, Dima Damen, Giovanni Maria Farinella, Christian Fuegen, Bernard Ghanem, Vamsi Krishna Ithapu, C. V. Jawahar, Hanbyul Joo, Kris Kitani, Haizhou Li, Richard Newcombe, Aude Oliva, Hyun Soo Park, James M. Rehg, Yoichi Sato, Jianbo Shi, Mike Zheng Shou, Antonio Torralba, Lorenzo Torresani, Mingfei Yan, Jitendra Malik

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/

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facebookresearch/Ego4d officialmentioned on GitHubpytorchMIT report
ego4d/episodic-memory mentioned on GitHubpytorchMIT report
ego4d/forecasting mentioned on GitHubpytorchMIT report
ego4d/hands-and-objects mentioned on GitHub report
nnnnai/ego4d_nlq_2022_1st_place_solution mentioned on GitHubpytorchMIT report
pyannote/pyannote-audio mentioned on GitHubpytorch report
yeliudev/R2-Tuning mentioned on GitHubpytorchBSD-3-Clause report

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2ran · honoured contract
1ran · fixture could not drive it
6ran
6unverified

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bi_loss ego4d/episodic-memory/MQ/Models/Loss.py community (archive-listed) ran fingerprinted MIT (permissive) · 7ec8e5ea9abf1846 · report
convert_annotations_to_clipwise_list ego4d/episodic-memory/VQ2D/extract_vq_detection_scores.py community (archive-listed) ran MIT (permissive) · ca522943b8eb15aa · report
get_loss_supplement ego4d/episodic-memory/MQ/Models/Loss.py community (archive-listed) ran MIT (permissive) · 05a34cc547463ca5 · report
get_neigh_idx_semantic ego4d/episodic-memory/MQ/Models/GCNs.py community (archive-listed) ran MIT (permissive) · b00a3a1790c6e560 · report
nms ego4d/episodic-memory/MQ/Infer.py community (archive-listed) ran MIT (permissive) · 2ab50acb3969a597 · report
round_width ego4d/forecasting/ego4d_forecasting/models/video_model_builder.py community (archive-listed) ran MIT (permissive) · b07e3607b90c1e7c · report
wrapper_segment_iou ego4d/hands-and-objects/state-change-localization-classification/bmn/BMN-Boundary-Matching-Network/Evaluation/eval_proposal.py community (archive-listed) ran · honoured contract fingerprinted MIT (permissive) · 265572629e36af77 · report
drop_path ego4d/forecasting/ego4d_forecasting/models/video_model_builder.py community (archive-listed) unverified MIT (permissive) · bcc1cdae3bb3212c · report
get_loss_func ego4d/forecasting/ego4d_forecasting/models/losses.py community (archive-listed) unverified MIT (permissive) · dd72775d1ea00db7 · report
get_norm ego4d/forecasting/ego4d_forecasting/models/batchnorm_helper.py community (archive-listed) unverified MIT (permissive) · 952f23f7aff7ce7d · report
get_trans_func ego4d/forecasting/ego4d_forecasting/models/resnet_helper.py community (archive-listed) unverified MIT (permissive) · 4d6991202a8d6097 · report
is_detection_enabled ego4d/forecasting/ego4d_forecasting/models/video_model_builder.py community (archive-listed) unverified MIT (permissive) · a99430fceaa1dc2d · report
knn ego4d/episodic-memory/MQ/Models/GCNs.py community (archive-listed) unverified MIT (permissive) · 9a2621658570ef96 · report
interpolated_prec_rec identical code first harvested elsewhere ran · fixture could not drive it fingerprinted licence of this copy not recorded · 81aab88321de62c2 · report
segment_iou identical code first harvested elsewhere ran · honoured contract fingerprinted licence of this copy not recorded · d0744a2fe3151508 · report

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