 The idea is to add structures called “capsules” to a convolutional neural network (CNN), and to reuse output from several of those capsules to form more stable (with respect to various perturbations) representations for higher capsules.The output is a vector consisting of the probability of an observation, and a pose for that observation.This vector is similar to what is done for example when doing "classification with localization" in CNNs.