Mask R-CNN – Instance segmentation with CNN
Faster R-CNN is state-of-the-art stuff in object detection today. But there are problems overlapping the area of object detection that Faster R-CNN cannot solve effectively, which is where Mask R-CNN, an evolution of Faster R-CNN can help.
This section introduces the concept of instance segmentation, which is a combination of the standard object detection problem as described in this chapter, and the challenge of semantic segmentation.
Note
In semantic segmentation, as applied to images, the goal is to classify each pixel into a fixed set of categories without differentiating object instances.
Remember our example of counting the number of dogs in the image in the intuition section? We were able to count the number of dogs easily, because they were very much apart, with no overlap, so essentially just counting the number of objects did the job. Now, take the following image, for instance, and count the number of tomatoes using object detection. It...
