In recent times, text detection in the wild has significantly raised its ability due to tremendous success of deep learning models. Applications of computer vision have emerged and got reshaped in a new way in this booming era of deep learning. In the last decade, research community has witnessed drastic changes in the area of text detection from natural scene images in terms of approach, coverage and performance due to huge advancement of deep neural network based models. In this paper, we present (1) a comprehensive review of deep learning approaches towards scene text detection, (2) suitable deep frameworks for this task followed by critical analysis, (3) a categorical study of publicly available scene image datasets and applicable standard evaluation protocols with their pros and cons, and (4) comparative results and analysis of reported methods. Moreover, based on this review and analysis, we precisely mention possible future scopes and thrust areas of deep learning approaches towards text detection from natural scene images on which upcoming researchers may focus.