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

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 countri...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - PP(2024) vom: 26. Juli
1. Verfasser: Grauman, Kristen (VerfasserIn)
Weitere Verfasser: Westbury, Andrew, Byrne, Eugene, Cartillier, Vincent, Chavis, Zachary, Furnari, Antonino, Girdhar, Rohit, Hamburger, Jackson, Jiang, Hao, Kukreja, Devansh, Liu, Miao, Liu, Xingyu, Martin, Miguel, Nagarajan, Tushar, Radosavovic, Ilija, Ramakrishnan, Santhosh Kumar, Ryan, Fiona, Sharma, Jayant, Wray, Michael, Xu, Mengmeng, Xu, Eric Zhongcong, Zhao, Chen, Bansal, Siddhant, Batra, Dhruv, Crane, Sean, Do, Tien, Doulaty, Morrie, Erapalli, Akshay, Feichtenhofer, Christoph, Fragomeni, Adriano, Fu, Qichen, Gebreselasie, Abrham, Gonzalez, Cristina, Hillis, James, Huang, Xuhua, Huang, Yifei, Jia, Wenqi, Khoo, Weslie, Kolar, Jachym, Kottur, Satwik, Kumar, Anurag, Landini, Federico, Li, Chao, Li, Yanghao, Li, Zhenqiang, Mangalam, Karttikeya, Modhugu, Raghava, Munro, Jonathan, Murrell, Tullie, Nishiyasu, Takumi, Price, Will, Puentes, Paola Ruiz, Ramazanova, Merey, Sari, Leda, Somasundaram, Kiran, Southerland, Audrey, Sugano, Yusuke, Tao, Ruijie, Vo, Minh, Wang, Yuchen, Wu, Xindi, Yagi, Takuma, Zhao, Ziwei, Zhu, Yunyi, Arbelaez, Pablo, Crandall, David, Damen, Dima, Farinella, Giovanni Maria, Fuegen, Christian, Ghanem, Bernard, Ithapu, Vamsi Krishna, Jawahar, C V, Joo, Hanbyul, Kitani, Kris, Li, Haizhou, Newcombe, Richard, Oliva, Aude, Park, Hyun Soo, Rehg, James M, Sato, Yoichi, Shi, Jianbo, Shou, Mike Zheng, Torralba, Antonio, Torresani, Lorenzo, Yan, Mingfei, Malik, Jitendra
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2024
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article
Beschreibung
Zusammenfassung: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/
Beschreibung:Date Revised 30.07.2024
published: Print-Electronic
Citation Status Publisher
ISSN:1939-3539
DOI:10.1109/TPAMI.2024.3381075