Visual Question Answering using Deep Learning: A Survey and Performance Analysis
The Visual Question Answering (VQA) task combines challenges for processing data with both Visual and Linguistic processing, to answer basic `common sense' questions about given images. Given an image and a question in natural language, the VQA system tries to find the correct answer to it using visual elements of the image and inference gathered from textual questions. In this survey, we cover and discuss the recent datasets released in the VQA domain dealing with various types of question-formats and robustness of the machine-learning models. Next, we discuss about new deep learning models that have shown promising results over the VQA datasets. At the end, we present and discuss some of the results computed by us over the vanilla VQA model, Stacked Attention Network and the VQA Challenge 2017 winner model. We also provide the detailed analysis along with the challenges and future research directions.
Code (1)
Tasks
Common Sense ReasoningQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)Similar Papers 제목 키워드 기반
Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature
Visual Question Answering (VQA) is an emerging area of interest for researches, being a recent problem in natural language processing and image prediction. In this area, an algorithm needs to answer questions about certa…
Question AnsweringVisual Question AnsweringVisual Question Answering (VQA)Chart Question Answering: State of the Art and Future Directions
Information visualizations such as bar charts and line charts are very common for analyzing data and discovering critical insights. Often people analyze charts to answer questions that they have in mind. Answering such q…
Chart Question AnsweringQuestion AnsweringSurvey on Question Answering over Visually Rich Documents: Methods, Challenges, and Trends
Using Large Language Models (LLMs) for Visually-rich Document Understanding (VrDU) has significantly improved performance on tasks requiring both comprehension and generation, such as question answering, albeit introduci…
document understandingQuestion AnsweringSurveySurvey of Recent Advances in Visual Question Answering
Visual Question Answering (VQA) presents a unique challenge as it requires the ability to understand and encode the multi-modal inputs - in terms of image processing and natural language processing. The algorithm further…
Question AnsweringSurveyVisual Question AnsweringVisual Question Answering (VQA)Survey of Visual Question Answering: Datasets and Techniques
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 tac…
Deep LearningQuestion AnsweringSurveyVisual Question Answering+1