It has very much been fitted. The supplementary material describes the training set as 5 pictures each of 2M different scenes of the type you can see in the paper (square room with random objects).

So to extrapolate wildly, it seems reasonable that getting similar results for, say, real-world bedrooms, you'd need to take around 5 pics each of 2M bedrooms, and record the location and angle of the camera for each picture.

Edit: and I didn't mean to sound negative, using artificially generated rooms to develop the method is a great idea, and the next step will be narrow domain specific applications (they mention eg robotic arms) where it's feasible to automatically collect enough data for a task, and somewhere in the future we may have the data and compute to sample the distribution of real world environments in decent resolution..