Review of Deep Learning Based Object Detection Methods and Their Mainstream Frameworks

As one of the important tasks in machine vision, object detection is a technology branch with important research value in artificial intelligence systems. The three mainstream object detection models of convolutional neural network framework, anchor-based model, and anchor-free model arc analyzed. First, the network structure and the advantages and disadvantages of the mainstream convolutional neural network framework, and the related improvement methods are reviewed. Second, the anchor-based model is deeply analyzed from one-stage and two-stage branches, and the research progresses of different object detection methods are summarized. The anchor-free model is analyzed from three parts: early exploration, key points, and intensive prediction. Finally, the future development trend of the field is considered and prospected.