Yes, I saw that they are, but at that point, I'd have to ask where the novelty is besides transforming them from probabilistic problems to plain neural-network problems.
I would call "inverse graphics" a task. One can solve that task following different strategies. We demonstrate one way that uses RL and GANs and gives reasonably good results. For Omniglot, for example, there are works by Lake et al. that employ probabilistic perspective but the amount of hand-engineering involved makes their approach hard to apply to other tasks
