Maybe I'm oversimplifying but this seems like an obviously simple* problem to solve: as humans, before we can identify what objects are, we start out with depth

Maybe I'm oversimplifying but this seems like an obviously simple* problem to solve: as humans, before we can identify what objects are, we start out with depth perception and object detection. If NNs were trained on a dataset of imagery where autodetected object outlines were tagged, rather than simply tagging or describing an entire image, and then run with built in object detection and depth perception, I suspect the results would be pretty good. I know the likes of Google and Facebook are already doing precisely this with human faces, but we'd need a more generalised object detection algorithm before the examples of sheep in the article would be reliably identified. * I used the word "simple", as distinct from "easy": for example, creating a training dataset might be a challenge.