A Survey of Modern Deep Learning based Object Detection Models
Computer Vision and Pattern Recognition
2021-05-13 v2 Machine Learning
Image and Video Processing
Abstract
Object Detection is the task of classification and localization of objects in an image or video. It has gained prominence in recent years due to its widespread applications. This article surveys recent developments in deep learning based object detectors. Concise overview of benchmark datasets and evaluation metrics used in detection is also provided along with some of the prominent backbone architectures used in recognition tasks. It also covers contemporary lightweight classification models used on edge devices. Lastly, we compare the performances of these architectures on multiple metrics.
Cite
@article{arxiv.2104.11892,
title = {A Survey of Modern Deep Learning based Object Detection Models},
author = {Syed Sahil Abbas Zaidi and Mohammad Samar Ansari and Asra Aslam and Nadia Kanwal and Mamoona Asghar and Brian Lee},
journal= {arXiv preprint arXiv:2104.11892},
year = {2021}
}
Comments
Preprint submitted to IET Computer Vision