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Video Moment Localization Network Based on Text Multi-semantic Clues GuidanceWU, G.   , XU, T. |
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Author keywords
information retrieval, machine learning, computer vision, natural language processing, pattern matching
References keywords
vision(24), video(16), cvpr(16), temporal(14), moment(14), localization(14), recognition(12), language(12), iccv(12), videos(11)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2023-08-31
Volume 23, Issue 3, Year 2023, On page(s): 85 - 92
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.03010
Web of Science Accession Number: 001062641900010
SCOPUS ID: 85172352256
Abstract
With the rapid development of the Internet and information technology, people are able to create multimedia data such as pictures or videos anytime and anywhere. Efficient multimedia processing tools are needed for the vast video data. The video moment localization task aims to locate the video moment which best matches the query in the untrimmed video. Existing text-guided methods only consider single-scale text features, which cannot fully represent the semantic features of text, and also do not consider the masking of crucial information in the video by text information when using text to guide the extraction of video features. To solve the above problems, we propose a video moment localization network based on text multi-semantic clues guidance. Specifically, we first design a text encoder based on fusion gate to better capture the semantic information in the text through multi-semantic clues composed of word embedding, local features and global features. Then text guidance module guides the extraction of video features by text semantic features to highlight the video features related to text semantics. Experimental results on two datasets, Charades-STA and ActivityNet Captions, show that our approach provides significant improvements over state-of-the-art methods. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
