  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.
