Advanced Object Detection

In the previous chapter, we learned about R-CNN and Fast R-CNN techniques, which leveraged region proposals to generate predictions of the locations of objects in an image along with the classes corresponding to objects in the image. Furthermore, we learned about the bottleneck of the speed of inference, which happens because of having two different models – one for region proposal generation and another for object detection. In this chapter, we will learn about different modern techniques, such as Faster R-CNN, YOLO, and Single-Shot Detector (SSD), that overcome slow inference time by employing a single model to make predictions for both the class of object and the bounding box in a single shot. We will start by learning about anchor boxes and then proceed to learn about how each of the techniques works and how to implement them to detect objects...