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.
翻译:物体探测是图像或视频中物体分类和定位的任务,近年来由于其广泛应用而越来越突出。本文章调查了基于深学习的物体探测器的最新发展情况。还提供了用于探测的基准数据集和评估指标的简明概览,以及用于识别任务的一些突出的骨干结构。它还涵盖了用于边缘装置的当代轻量级分类模型。最后,我们将这些结构的性能与多个指标进行比较。