Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature
It synthesizes trends for researchers in VQA, but is incremental as a survey.
This survey analyzes 25 recent studies and 6 datasets in Visual Question Answering (VQA), providing comparisons of results, state-of-the-art methods, common errors, and improvement points.
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 certain images. As of the writing of this survey, 25 recent studies were analyzed. Besides, 6 datasets were analyzed and provided their link to download. In this work, several recent pieces of research in this area were investigated and a deeper analysis and comparison among them were provided, including results, the state-of-the-art, common errors, and possible points of improvement for future researchers.