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Paper on Moment Localization from Video Corpus accepted in IEEE T-IP 2021

Instead of traditional text-based moment localization from a given video, this paper addresses a realistic and challenging problem of text-based localization of moments in a video corpus.

Given a text query, retrieving the relevant video segments is an important and challenging problem. While many methods have looked at this problem for individual videos, our work is the first that considers a video corpus. We propose a hierarchical approach that considers intra-video and inter-video semantic relationships. More details can be found in our paper here.