Review of Object Detection Techniques

被引：0

作者：

Yu Boyang ^{[1
]}

Jin Feng ^{[1
]}

Dong Lei ^{[1
]}

Gao Mengqi ^{[1
]}

Jia Yanbo ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

来源：

2022 41ST CHINESE CONTROL CONFERENCE (CCC) | 2022年

关键词：

Computer Vision; Deep Learning; Object Detection; Convolutional Neural Networks; Transformer;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

As the front-end technology of artificial intelligence, computer vision has been widely studied in recent years, and the introduction of deep learning methods has accelerated this process. This paper shows the progress made in object detection in the last 5 years, followed by the mainstream model topology including Convolutional Neural Network and Transformer. We further compared the accuracy and model complexity of different backbones, analyzed the differences and the inner link between Convolutional Neural Network and Transformer, at the end of the thesis, the prospect of future development is presented.

引用

页码：7136 / 7143

页数：8

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