CONE: An efficient COarse-to-fiNE alignment framework for long video temporal grounding

CONE: An efficient COarse-to-fiNE alignment framework for long video temporal grounding

This paper tackles an emerging and challenging problem of long video temporal grounding (VTG) that localizes video moments related to a natural language (NL) query. Compared with short videos, long videos are also highly demanded but less explored, which brings new challenges in higher inference com...

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Bibliographic Details
Main Authors: HOU, Zhijian, ZHONG, Wanjun, JI, Lei, GAO, Difei, YAN, Kun, CHAN, Wing-Kwong, NGO, Chong-Wah, SHOU, Mike Z., DUAN, Nan.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
Subjects:
Benchmarking
Computational linguistics
Natural language processing systems
Artificial Intelligence and Robotics
Online Access:https://ink.library.smu.edu.sg/sis_research/8375
https://ink.library.smu.edu.sg/context/sis_research/article/9378/viewcontent/2023.acl_long.445.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/8375
https://ink.library.smu.edu.sg/context/sis_research/article/9378/viewcontent/2023.acl_long.445.pdf

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