  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, computer vision, and natural language processing. Much of the growth
in these fields has been made possible with deep learning, a sub-area of
machine learning that uses artificial neural networks. This has created
significant interest in the integration of vision and language. In this survey,
we focus on ten prominent tasks that integrate language and vision by
discussing their problem formulation, 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 stimulates innovative thoughts
and ideas to address the existing challenges and build new applications.
