  Deep Learning and its applications have cascaded impactful research and
development with a diverse range of modalities present in the real-world data.
More recently, this has enhanced research interests in the intersection of the
Vision and Language arena with its numerous applications and fast-paced growth.
In this paper, we present a detailed overview of the latest trends in research
pertaining to visual and language modalities. We look at its applications in
their task formulations and how to solve various problems related to semantic
perception and content generation. We also address task-specific trends, along
with their evaluation strategies and upcoming challenges. Moreover, we shed
some light on multi-disciplinary patterns and insights that have emerged in the
recent past, directing this field towards more modular and transparent
intelligent systems. This survey identifies key trends gravitating recent
literature in VisLang research and attempts to unearth directions that the
field is heading towards.
