As mentioned in the question, i've noticed that sometimes there are pooling layers with padding.
More specifically, I found this Keras tutorial, where there's a net which contains
MaxPooling layers with padding.
padding=same in convolutional layers, our output size (at least height and width, depth can change based on the number of filters) is the same as the input.
I expected the same with the
MaxPooling layer, but Keras
model.summary() (as shown in the article) shows that the output size after the pooling layers is half of the input.
What's the point of adding padding to the Pooling layer if we still get an output which is half of the input?