多模态理解的预训练模型》特约编辑导言

IF 8.4 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Transactions on Multimedia Pub Date : 2024-07-31 DOI:10.1109/TMM.2024.3384680
Wengang Zhou;Jiajun Deng;Niculae Sebe;Qi Tian;Alan L. Yuille;Concetto Spampinato;Zakia Hammal
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引用次数: 0

摘要

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