Wide-field sub-millimetre surveys have driven many major advances in galaxy evolution in the past decade, but without extensive follow-ups the coarse angular resolution of these surveys limits the science exploitation. This has driven many deconvolution efforts. Generative Adversarial Networks have already been used to attempt deconvolutions on optical data. In this talk I will present an autoencoder with a novel loss function to overcome this problem at submm wavelengths. This approach is successfully demonstrated on Herschel SPIRE COSMOS data, with the super-resolving target being the JCMT SCUBA-2 observations of the same field. We reproduce the JCMT SCUBA-2 images with surprisingly high fidelity, and quantify the point source flux constraints using this autoencoder.