Image regression problem
Couple of Things straight up:

Inject some noise in the process. When the gan or autoencoder learns that there is some noise it will start to generalise better

Use weaker architectures. (Analogy to weak learners, you cant build random forest wit hstrong trees). Basically allowing for your Architecture to be weak enough to be able to generalise and not learn everything by heart, i.e. map Input to Output.