Visual Question Answering: From Theory to Application

Visual Question Answering: From Theory to Application (Advances in Computer Vision and Pattern Recognition) 1st ed. 2022 Edition
Author: Qi Wu,Peng Wang,Xin Wang,Xiaodong He,Wenwu Zhu (Author)
Publisher Finelybook 出版社:Springer; 1st ed. 2022 edition (May 14, 2022)
Language 语言:English
pages 页数:251 pages
ISBN-10 书号:9811909636
ISBN-13 书号:9789811909634

Book Description
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 Author: 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 Author: using large-scale databases with mixed-quality inputs. However, with the advent of deep learning (DL) and driven Author: 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.

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