# What is the difference between FC and MLP in as used in PointNet?

I am trying to understand the PointNet network for dealing with point clouds and struggling with understanding the difference between FC and MLP:

"FC is fully connected layer operating on each point. MLP is multi-layer perceptron on each point."

I understand how fully connected layers are used to classify and I previously thought, was that MLP was the same thing but it seems varying academic papers have a differing definition from each other and from general online courses. In PointNet what is meant by a shared MLP different to a standard feedforward fully connected network?