Attention Mechanism has now become an important concept in neural networks that has been researched within diverse application domains. This survey provides a systematic and comprehensive overview of the developments in attention modeling. The attention mechanism simulates the mechanism of human visual selectivity, and its core goal is to select the more relevant and critical information from the tedious information for the current target task. It is also an efficient information selection and attention mechanism. It has been widely used in deep learning studies in recent years and plays a pivotal role in natural language processing, speech recognition, and computer vision. This article first briefly introduces the origin of attention mechanism, then summarizes the structure of various attention mechanisms and their latest developments, and finally summarizes their role in multiple application areas. At the same time, it summarizes the future development direction of attention mechanisms and the challenges that will be faced.