I'm well aware of the inner workings of CNN models for object detection, and although I've not worked on a semantic segmentation problem I can imagine how it works.
With these types of models, we need to say "segment out the humans", or "segment out the X". But what about when I say something like "segment out the subject of this photo, whatever it happens to be". For example, see this service: https://removal.ai/
Without too much imagination I might guess that they apply a multiclass segmentation model and just show any foreground pixels, no matter what class they belong to. So we'd hope that the subject is in one of the classes that the model was trained for, and that there are no other class instances in the image that shouldn't be captured. But is there a more general way?