目标检测综述，做一些笔记记录一下
一、INTRODUCTION
1、From the application point of view, object detection can be grouped into two research topics “general object detection” and “detection applications”, where the former one aims to explore the methods of detecting different types of objects under a unified framework to simulate the human vision and cognition, and the later one refers to the detection under specific application scenarios, such as pedestrian detection,face detection, text detection, etc.
2、 After years of development,the state of the art object detection systems have been integrated with a large number of techniques such as “multiscale detection”, “hard negative mining”, “bounding box regression”, etc.
3、 The acceleration of object detection has long been a crucial but challenging task.
4、As different detection tasks have totally different objectives and constraints, their difficulties may vary from each other. In addition to some common challenges in other computer vision tasks such as objects under different viewpoints,illuminations, and intraclass variations, the challenges in object detection include but not limited to the following aspects: object rotation and scale changes (e.g., small objects), accurate object localization, dense and occluded object detection, speed up of detection, etc.
二、OBJECT DETECTION IN 20 YEARS
1、In the past two decades, it is widely accepted that the progress of object detection has generally gone through two historical periods: “traditional object detection period (before 2014)” and “deep learning based detection period (after 2014)”
未完待续……