Mogadala, Aditya; Kalimuthu, Marimuthu; Klakow, Dietrich
Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
Journal of Artificial Intelligence Research, 71, Access Foundation, pp. 1183-1317, 2021.
The interest in Artificial Intelligence (AI) and its applications has seen unprecedented growth in the last few years. This success can be partly attributed to the advancements made in the sub-fields of AI such as Machine Learning (ML), Computer Vision (CV), and Natural Language Processing (NLP). The largest of the growths in these fields has been made possible with deep learning, a sub-area of machine learning, which uses the principles of artificial neural networks. This has created significant interest in the integration of vision and language. The tasks are designed such that they perfectly embrace the ideas of deep learning. In this survey, we focus on ten prominent tasks that integrate language and vision by discussing their problem formulations, methods, existing datasets, evaluation measures, and compare the results obtained with corresponding state-of-the-art methods. Our efforts go beyond earlier surveys which are either task-specific or concentrate only on one type of visual content, i.e., image or video. Furthermore, we also provide some potential future directions in this field of research with an anticipation that this survey brings in innovative thoughts and ideas to address the existing challenges and build new applications.