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This technical report describes the CONE approach for Ego4D Natural Language Queries (NLQ) Challenge in ECCV 2022.
Span-based localizing network for natural language video localization
Hao Zhang, Aixin Sun, Wei Jing, and Joey Tianyi Zhou · 2020
Earlier work this paper cites.
Detecting moments and highlights in videos via natural language queries
Jie Lei, Tamara L Berg, and Mohit Bansal · 2021
Earlier work this paper cites.
Ego4d: Around the world in 3,000 hours of egocentric video
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, et al · 2022
Cited alongside, same era.
Cone: An efficient coarse-to-fine alignment framework for long video temporal grounding
Zhijian Hou, Wanjun Zhong, Lei Ji, Difei Gao, Kun Yan, Wing-Kwong Chan, Chong-Wah Ngo, Zheng Shou, and Nan Duan · 2022
Cited alongside, same era.
Egocentric video-language pretraining
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan, Michael Wray, Rui Yan, Eric Zhongcong Xu, Difei Gao, Rongcheng Tu, Wenzhe Zhao, Weijie Kong, et al · 2022
Closest in time.
Reler@ zju-alibaba submission to the ego4d natural language queries challenge 2022
Naiyuan Liu, Xiaohan Wang, Xiaobo Li, Yi Yang, and Yueting Zhuang · 2022
Closest in time.
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