High-level features of a neural network
Its about how the neural net learn inside. Usually in deep neural network you have multiple layers, the first layers will learn the low level feature then the more you approach the output layer the more the layers will learn the high level feature. 
Here its identifying faces task, that's why you see that in the first layers small patterns are learned (mainly edges ...) then faces components ...

How to obtain them : you should watch what makes neuron activated in each layer depending on the input. As you know each neuron will be activated (once the DNN is trained) for specific input combinations. 
By visualizing that you can get an idea about what exactly each layer has learned in term of high-low level features.