Guest Editorial Introduction to the Issue on Pre-Trained Models for Multi-Modality Understanding

IF 8.4 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Wengang Zhou;Jiajun Deng;Niculae Sebe;Qi Tian;Alan L. Yuille;Concetto Spampinato;Zakia Hammal
{"title":"Guest Editorial Introduction to the Issue on Pre-Trained Models for Multi-Modality Understanding","authors":"Wengang Zhou;Jiajun Deng;Niculae Sebe;Qi Tian;Alan L. Yuille;Concetto Spampinato;Zakia Hammal","doi":"10.1109/TMM.2024.3384680","DOIUrl":null,"url":null,"abstract":"In the ever-evolving domain of multimedia, the significance of multi-modality understanding cannot be overstated. As multimedia content becomes increasingly sophisticated and ubiquitous, the ability to effectively combine and analyze the diverse information from different types of data, such as text, audio, image, video and point clouds, will be paramount in pushing the boundaries of what technology can achieve in understanding and interacting with the world around us. Accordingly, multi-modality understanding has attracted a tremendous amount of research, establishing itself as an emerging topic. Pre-trained models, in particular, have revolutionized this field, providing a way to leverage vast amounts of data without task-specific annotation to facilitate various downstream tasks.","PeriodicalId":13273,"journal":{"name":"IEEE Transactions on Multimedia","volume":"26 ","pages":"8291-8296"},"PeriodicalIF":8.4000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10616245","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Multimedia","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10616245/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

In the ever-evolving domain of multimedia, the significance of multi-modality understanding cannot be overstated. As multimedia content becomes increasingly sophisticated and ubiquitous, the ability to effectively combine and analyze the diverse information from different types of data, such as text, audio, image, video and point clouds, will be paramount in pushing the boundaries of what technology can achieve in understanding and interacting with the world around us. Accordingly, multi-modality understanding has attracted a tremendous amount of research, establishing itself as an emerging topic. Pre-trained models, in particular, have revolutionized this field, providing a way to leverage vast amounts of data without task-specific annotation to facilitate various downstream tasks.
多模态理解的预训练模型》特约编辑导言
在不断发展的多媒体领域,多模态理解的重要性怎么强调都不为过。随着多媒体内容变得越来越复杂和无处不在,有效地组合和分析来自不同类型数据(如文本、音频、图像、视频和点云)的各种信息的能力,对于推动技术在理解我们周围的世界并与之互动方面所能达到的极限将是至关重要的。因此,多模态理解吸引了大量研究,成为一个新兴课题。预训练模型尤其为这一领域带来了革命性的变化,它提供了一种无需特定任务注释即可利用海量数据的方法,从而为各种下游任务提供了便利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IEEE Transactions on Multimedia
IEEE Transactions on Multimedia 工程技术-电信学
CiteScore
11.70
自引率
11.00%
发文量
576
审稿时长
5.5 months
期刊介绍: The IEEE Transactions on Multimedia delves into diverse aspects of multimedia technology and applications, covering circuits, networking, signal processing, systems, software, and systems integration. The scope aligns with the Fields of Interest of the sponsors, ensuring a comprehensive exploration of research in multimedia.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信