  In this chapter, we present a brief overview of the recent development in
object detection using convolutional neural networks (CNN). Several classical
CNN-based detectors are presented. Some developments are based on the detector
architectures, while others are focused on solving certain problems, like model
degradation and small-scale object detection. The chapter also presents some
performance comparison results of different models on several benchmark
datasets. Through the discussion of these models, we hope to give readers a
general idea about the developments of CNN-based object detection.
