Abstract
Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Its development in the past two decades can be regarded as an epitome of computer vision history. If we think of today's object detection as a technical aesthetics under the power of deep learning, then turning back the clock 20 years we would witness the wisdom of cold weapon era. This paper extensively reviews 400+ papers of object detection in the light of its technical evolution, spanning over a quarter-century's time (from the 1990s to 2019). A number of topics have been covered in this paper, including the milestone detectors in history, detection datasets, metrics, fundamental building blocks of the detection system, speed up techniques, and the recent state of the art detection methods. This paper also reviews some important detection applications, such as pedestrian detection, face detection, text detection, etc, and makes an in-deep analysis of their challenges as well as technical improvements in recent years.
Abstract (translated)
目标检测作为计算机视觉中最基本、最具挑战性的问题之一，近年来受到了广泛的关注。它在过去二十年的发展可以看作是计算机视觉历史的缩影。如果我们把今天的物体探测看作是一种在深度学习的力量下的技术美学，那么把时钟倒转20年，我们将见证冷武器时代的智慧。本文从技术发展的角度对400多篇对象检测论文进行了广泛的回顾，跨越了四分之一世纪的时间（从90年代到2019年）。本文涵盖了许多主题，包括历史上的里程碑探测器、检测数据集、度量、检测系统的基本构建块、加速技术和最新的检测方法。本文还综述了行人检测、人脸检测、文本检测等重要的检测应用，并对其面临的挑战和近年来的技术进步进行了深入分析。
URL
https://arxiv.org/abs/1905.05055
