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 toward 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 toward.

深度学习及其应用通过现实世界数据中存在的各种模式，将具有影响力的研究和开发级联起来。最近，这增强了对视觉和语言领域交叉点的研究兴趣，其众多应用程序和快速增长。在本文中，我们详细概述了与视觉和语言模式有关的研究的最新趋势。我们研究了它在任务制定中的应用，以及如何解决与语义感知和内容生成相关的各种问题。我们还解决了特定于任务的趋势，以及它们的评估策略和即将到来的挑战。此外，我们阐明了最近出现的多学科模式和见解，将该领域导向更模块化和更透明的智能系统。这项调查确定了吸引 VisLang 研究的近期文献的主要趋势，并试图发掘该领域正在走向的方向。