Visual Object Detection: A Review

Object detection is a vitally important fundamental task in computer vision, and is applied in a number of scenarios including autonomous driving, robots, and industrial detection. Since 2014, object detection has become a research focus with the introduction of deep learning, which attracted a lot of attention. Even though object detection has developed rapidly in recent years with the power of deep learning, the ideas and motivations of many new models are still inspired by traditional algorithms. Therefore, it is necessary to understand the technical evolution of object detection to grasp its future direction. This paper provides a short survey on object detection, focusing on a comprehensive review of the technical development history in the past two decades. Secondly, the characteristics of each development period are summarized and some research hotspots in recent three years are given out. Then, the typical applications of object detection are illustrated. Finally, the paper discusses the possible challenges and development directions of object detection in the future.