From both my own exploration of Google Deep Dream using Dreamify for IOS, and from Google Image results on the topic. I've come to 3 conclusions about the networks understanding of images that seem too common to be coincidences.
I would like to know if these are recognised as consequences of the approach, or otherwise to what degree thease properties are imagined while trying to understand the ambiguous high frequency images the Deep Dream algorithm often produces?
3 dimensional understanding of real and dreamt objects, including rotation, occlusion (close things covering distant things), reflections etc...
Understanding of how objects group and are arranged allowing deep dream to create believable landscapes, settlements and narrative and physical interactions, including between people.
Objects (including people) being thematically/stylistically designed to fit a scene.