Visual question answering :: from theory to application /: Qi Wu, Peng Wang, Xin Wang, Xiaodong He, Wenwu Zhu.

Wu, Qi,; Wang, Peng,; Wang, Xin,; He, Xiaodong,; Zhu, Wenwu,

doi:10.1007/978-981-19-0964-1

Visual question answering : from theory to application / Qi Wu, Peng Wang, Xin Wang, Xiaodong He, Wenwu Zhu.

Wu, Qi, author.; Wang, Peng, author.; Wang, Xin, author.; He, Xiaodong, 1973- author.; Zhu, Wenwu, author.

2022

TA1634

Available Online

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Details

Title

Visual question answering : from theory to application / Qi Wu, Peng Wang, Xin Wang, Xiaodong He, Wenwu Zhu.

Author

Wu, Qi, author.

ISBN

9789811909641 (electronic bk.)
9811909644 (electronic bk.)
9789811909634 (print)
9811909636

DOI

https://doi.org/10.1007/978-981-19-0964-1

Published

Singapore : Springer, 2022.

Language

English

Description

1 online resource (xiii, 238 pages) : illustrations (some color).

Item Number

10.1007/978-981-19-0964-1 doi

Call Number

TA1634

Dewey Decimal Classification

006.3/7

Summary

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, and promising 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 highlights the key models used in VQA.

Bibliography, etc. Note

Includes bibliographical references and index.

Access Note

Access limited to authorized users.

Source of Description

Online resource; title from PDF title page (SpringerLink, viewed May 20, 2022).

Added Author

Wang, Peng, author.
Wang, Xin, author.
He, Xiaodong, 1973- author.
Zhu, Wenwu, author.

Series

Advances in computer vision and pattern recognition.

Available in Other Form

Print version: 9789811909634