Good question. Neural networks are modelled after how brains learn and process information, so it's certainly theoretically possible for a neural network (or other machine learning algorithm) to make inferences like that, just like how you've learned them with years of experience.

The biggest challenge in any machine learning is finding enough labelled training data. In fact, a friend of mine contributed to a paper in which (no joke) GTA V was used to generate labelled training data for an automous vehicle. Because it's a game engine, every object in the game is already digitized, and the 3D modelling is accurate enough to be useful, at least. This vehicle used LIDAR so the actual shaders and such didn't matter as much as the 3D point cloud.