视觉语言预训练:基础、最新进展和未来趋势

IF 3.8 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Zhe Gan, Linjie Li, Chunyuan Li, Lijuan Wang, Zicheng Liu, Jianfeng Gao
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引用次数: 70

摘要

本文综述了近年来发展起来的多模态智能的视觉语言预训练方法。我们将这些方法分为三类:(i) VLP用于图像-文本任务,如图像字幕、图像-文本检索、视觉问答和视觉基础;($ii$) VLP用于核心计算机视觉任务,如(开集)图像分类、目标检测和分割;($iii$) VLP用于视频文本任务,如视频字幕、视频文本检索和视频问答。对于每个类别,我们都对最先进的方法进行了全面的回顾,并讨论了已经取得的进展和仍然面临的挑战,使用特定的系统和模型作为案例研究。此外,对于每个类别,我们讨论了在研究界正在积极探索的高级主题,例如大基础模型,统一建模,上下文少量学习,知识,鲁棒性和野外计算机视觉,等等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vision-Language Pre-training: Basics, Recent Advances, and Future Trends
This paper surveys vision-language pre-training (VLP) methods for multimodal intelligence that have been developed in the last few years. We group these approaches into three categories: ($i$) VLP for image-text tasks, such as image captioning, image-text retrieval, visual question answering, and visual grounding; ($ii$) VLP for core computer vision tasks, such as (open-set) image classification, object detection, and segmentation; and ($iii$) VLP for video-text tasks, such as video captioning, video-text retrieval, and video question answering. For each category, we present a comprehensive review of state-of-the-art methods, and discuss the progress that has been made and challenges still being faced, using specific systems and models as case studies. In addition, for each category, we discuss advanced topics being actively explored in the research community, such as big foundation models, unified modeling, in-context few-shot learning, knowledge, robustness, and computer vision in the wild, to name a few.
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来源期刊
Foundations and Trends in Computer Graphics and Vision
Foundations and Trends in Computer Graphics and Vision COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
31.20
自引率
0.00%
发文量
1
期刊介绍: The growth in all aspects of research in the last decade has led to a multitude of new publications and an exponential increase in published research. Finding a way through the excellent existing literature and keeping up to date has become a major time-consuming problem. Electronic publishing has given researchers instant access to more articles than ever before. But which articles are the essential ones that should be read to understand and keep abreast with developments of any topic? To address this problem Foundations and Trends® in Computer Graphics and Vision publishes high-quality survey and tutorial monographs of the field. Each issue of Foundations and Trends® in Computer Graphics and Vision comprises a 50-100 page monograph written by research leaders in the field. Monographs that give tutorial coverage of subjects, research retrospectives as well as survey papers that offer state-of-the-art reviews fall within the scope of the journal.
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