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

• المؤلفون الرئيسيون: HOU, Zhijian, ZHONG, Wanjun, JI, Lei, GAO, Difei, YAN, Kun, CHAN, Wing-Kwong, NGO, Chong-Wah, SHOU, Mike Z., DUAN, Nan.
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2023
• الموضوعات: Benchmarking; Computational linguistics; Natural language processing systems; Artificial Intelligence and Robotics
• الوصول للمادة أونلاين: 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

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...