Useful in the self-driving cars or autonomous cars for object detection and surveillance drones too, where the pixel to pixel accuracy matters and affects the total accuracy of models.
Instance Segmentation is used to identify the different instances belonging to the same class. This is applicable to train perception models for the feature detection in a scene. The instance segmentation problem precisely detects and delineates the objects in images. Most of the current solutions rely on deep convolutional neural networks but despite this fact proposed solutions are very diverse.
This is a combined result of instance and semantic segmentation. It classifies every pixel of an image and assigns a unique ID to each object belonging to the same class. Panoptic Segmentation requires a scene to not only be broken down semantically but also requires that each instance of a class, say a car or person, be labeled uniquely.