找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Visual Question Answering; From Theory to Appli Qi Wu,Peng Wang,Wenwu Zhu Book 2022 The Editor(s) (if applicable) and The Author(s), under

[复制链接]
查看: 42600|回复: 55
发表于 2025-3-21 16:26:57 | 显示全部楼层 |阅读模式
书目名称Visual Question Answering
副标题From Theory to Appli
编辑Qi Wu,Peng Wang,Wenwu Zhu
视频video
概述Provides the first comprehensive survey of and handbook on visual question answering (VQA).Is self-contained and reader-friendly: ranging from basic ML and NLP concepts and theory, to details of VQA a
丛书名称Advances in Computer Vision and Pattern Recognition
图书封面Titlebook: Visual Question Answering; From Theory to Appli Qi Wu,Peng Wang,Wenwu Zhu Book 2022 The Editor(s) (if applicable) and The Author(s), under
描述.Visual Question Answering (VQA) usually combines visual inputs like image and video with a natural language question concerning the input and generates a natural language answer as the output. This is by nature a multi-disciplinary research problem, involving computer vision (CV), natural language processing (NLP), knowledge representation and reasoning (KR), etc...Further, VQA is an ambitious undertaking, as it must overcome the challenges of general image understanding and the question-answering task, as well as the difficulties entailed by using large-scale databases with mixed-quality inputs. However, with the advent of deep learning (DL) and driven by the existence of advanced techniques in both CV and NLP and the availability of relevant large-scale datasets, we have recently seen enormous strides in VQA, with more systems and promising results emerging...This book provides a comprehensive overview of VQA, covering fundamental theories, models, datasets, andpromising future directions. Given its scope, it can be used as a textbook on computer vision and natural language processing, especially for researchers and students in the area of visual question answering. It also high
出版日期Book 2022
关键词Visual Question Answering; VQA; Image-based Question Answering; Vision-and-Language; Deep Learning
版次1
doihttps://doi.org/10.1007/978-981-19-0964-1
isbn_softcover978-981-19-0966-5
isbn_ebook978-981-19-0964-1Series ISSN 2191-6586 Series E-ISSN 2191-6594
issn_series 2191-6586
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

书目名称Visual Question Answering影响因子(影响力)




书目名称Visual Question Answering影响因子(影响力)学科排名




书目名称Visual Question Answering网络公开度




书目名称Visual Question Answering网络公开度学科排名




书目名称Visual Question Answering被引频次




书目名称Visual Question Answering被引频次学科排名




书目名称Visual Question Answering年度引用




书目名称Visual Question Answering年度引用学科排名




书目名称Visual Question Answering读者反馈




书目名称Visual Question Answering读者反馈学科排名




单选投票, 共有 0 人参与投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用户组没有投票权限
发表于 2025-3-21 21:13:42 | 显示全部楼层
发表于 2025-3-22 00:46:19 | 显示全部楼层
Deep Learning BasicsDeep learning basics are essential for the visual question answering task since multimodal information is usually complex and multidimensional. Therefore, in this chapter, we present basic information regarding deep learning, covering the following:
发表于 2025-3-22 07:56:47 | 显示全部楼层
Visual Question GenerationTo explore how questions regarding images are posed and abstract the events caused by objects in the image, the visual question generation (VQG) task has been established. In this chapter, we classify VQG methods according to whether their objective is data augmentation or visual understanding.
发表于 2025-3-22 08:51:12 | 显示全部楼层
Qi Wu,Peng Wang,Wenwu ZhuProvides the first comprehensive survey of and handbook on visual question answering (VQA).Is self-contained and reader-friendly: ranging from basic ML and NLP concepts and theory, to details of VQA a
发表于 2025-3-22 15:32:42 | 显示全部楼层
发表于 2025-3-22 18:17:10 | 显示全部楼层
Advanced Models for Video Question Answeringexist beyond this framework, which exhibit fine architectures and performances. In this chapter, we categorize these methods into four categories, i.e., ., . and . and discuss the characteristics of these frameworks.
发表于 2025-3-22 21:13:47 | 显示全部楼层
Advances in Computer Vision and Pattern Recognitionhttp://image.papertrans.cn/v/image/983777.jpg
发表于 2025-3-23 01:35:46 | 显示全部楼层
https://doi.org/10.1007/978-981-19-0964-1Visual Question Answering; VQA; Image-based Question Answering; Vision-and-Language; Deep Learning
发表于 2025-3-23 08:52:14 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-4 10:59
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表