Very interesting. I'm wondering whether statistics-based photo synthesis is actually viable. The main problem is that many kinds of scenes appear to require a p

Very interesting. I'm wondering whether statistics-based photo synthesis is actually viable. The main problem is that many kinds of scenes appear to require a precise geometrical understanding, e.g. sharp shadows that get cast on detailed surfaces by a desk lamp, or that a mirror would precisely reflect another object in the scene from a different angle. On the other hand, we don't require absolute precision, it just needs to be plausible enough to fool our eyes. If a shadow just looks roughly like the object that it casts, that should be enough. It seems to me that this still would require at least a rudimentary geometrical understanding/abstraction which will possibly require in comparison to this technique extremely sophisticated neural networks that can perform things like mental rotation, path integration, object recognition and have an understanding of object permanence.