计算机科学
对象(语法)
目标检测
算法
阶段(地层学)
人工智能
计算机视觉
模式识别(心理学)
古生物学
生物
作者
Peng He,Weidong Chen,Lan Pang,Weiguo Zhang,Yitian Wang,Weidong Huang,Qi Han,Xiaofeng Xu,Yuan Qi
摘要
With the improvement of computer computing power, the object detection algorithms based on deep neural network has ushered in vigorous development, and has been widely used in industry, agriculture, medicine, military and other fields. One-stage object detection algorithms shows the superiority in real-time detection compared to other object detection algorithms such as two-stage object detectors or ViT-based detectors. At the same time, more and more anchor-free detectors show the advanced nature of anchor-free algorithms compared to anchor-based detectors. In this paper, we review the one-stage anchor-free real-time object detection algorithms in recent years, and analyze the application scenarios and optimization strategies of future object detection algorithms. Firstly, the principle and advantages of anchor-free object detection algorithms and one-stage object detection algorithm are introduced. Secondly, the network structure and innovation of anchor-free object detection algorithms in recent years are summarized. Finally, the possible development direction and trend of one-stage anchor-free real-time object detection algorithms in the future are proposed.
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