A Review of Object Detection Models based on Convolutional Neural Network
This is an incremental review summarizing existing methods for researchers in computer vision.
The paper reviews state-of-the-art object detection models based on Convolutional Neural Networks, categorizing them into two-stage and one-stage approaches and comparing advancements from R-CNN to RefineDet.
Convolutional Neural Network (CNN) has become the state-of-the-art for object detection in image task. In this chapter, we have explained different state-of-the-art CNN based object detection models. We have made this review with categorization those detection models according to two different approaches: two-stage approach and one-stage approach. Through this chapter, it has shown advancements in object detection models from R-CNN to latest RefineDet. It has also discussed the model description and training details of each model. Here, we have also drawn a comparison among those models.