目标检测
计算机科学
重要事件
人工智能
领域(数学)
透视图(图形)
对象(语法)
深度学习
数据科学
加速
计算机视觉
模式识别(心理学)
地图学
地理
操作系统
纯数学
数学
作者
Zhengxia Zou,Keyan Chen,Zhenwei Shi,Yuhong Guo,Jieping Ye
出处
期刊:Proceedings of the IEEE
[Institute of Electrical and Electronics Engineers]
日期:2023-01-27
卷期号:111 (3): 257-276
被引量:1128
标识
DOI:10.1109/jproc.2023.3238524
摘要
Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Over the past two decades, we have seen a rapid technological evolution of object detection and its profound impact on the entire computer vision field. If we consider today’s object detection technique as a revolution driven by deep learning, then, back in the 1990s, we would see the ingenious thinking and long-term perspective design of early computer vision. This article extensively reviews this fast-moving research field in the light of technical evolution, spanning over a quarter-century’s time (from the 1990s to 2022). A number of topics have been covered in this article, including the milestone detectors in history, detection datasets, metrics, fundamental building blocks of the detection system, speedup techniques, and recent state-of-the-art detection methods.
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