Object Detection with Convolutional Neural Networks
It summarizes existing methods for researchers, but is incremental as it reviews prior work without introducing new findings.
This chapter provides an overview of recent developments in object detection using convolutional neural networks, discussing various models and their performance on benchmark datasets.
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.