Visual question answering: Datasets, algorithms, and future challenges
نویسندگان
چکیده
منابع مشابه
Visual question answering: Datasets, algorithms, and future challenges
Visual Question Answering (VQA) is a recent problem in computer vision and natural language processing that has garnered a large amount of interest from the deep learning, computer vision, and natural language processing communities. In VQA, an algorithm needs to answer text-based questions about images. Since the release of the first VQA dataset in 2014, several additional datasets have been r...
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Visual Question Answering (VQA) is a challenging task that has received increasing attention from both the computer vision and the natural language processing communities. Given an image and a question in natural language, it requires reasoning over visual elements of the image and general knowledge to infer the correct answer. In the first part of this survey, we examine the state of the art b...
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Visual question answering (or VQA) is a new and exciting problem that combines natural language processing and computer vision techniques. We present a survey of the various datasets and models that have been used to tackle this task. The first part of this survey details the various datasets for VQA and compares them along some common factors. The second part of this survey details the differe...
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ژورنال
عنوان ژورنال: Computer Vision and Image Understanding
سال: 2017
ISSN: 1077-3142
DOI: 10.1016/j.cviu.2017.06.005