Unsupervised Joint Image Transfer and Uncertainty Quantification Using Patch Invariant Networks. (arXiv:2207.04325v2 [cs.CV] UPDATED)

Unsupervised image transfer enables intra- and inter-modality image
translation in applications where a large amount of paired training data is not
abundant. To ensure a structure-preserving mapping from the input to the target
domain, existing methods for unpaired image transfer are commonly based on
cycle-consistency, causing additional computational resources and instability
due to the learning of an inverse mapping. This paper presents a novel method
for uni-directional domain mapping that does not rely on any paired training
data. A proper …

arxiv image networks quantification transfer uncertainty unsupervised