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Found 3 papers, 2 papers with code
Beyond Deterministic Translation for Unsupervised Domain Adaptation
In this work we challenge the common approach of using a one-to-one mapping ('translation') between the source and target domains in unsupervised domain adaptation (UDA).
Unsupervised Domain Adaptation with Semantic Consistency across Heterogeneous Modalities for MRI Prostate Lesion Segmentation
Firstly, we introduce a semantic cycle-consistency loss in the source domain to ensure that the translation preserves the semantics.
Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation
Domain adaptation methods partially mitigate this problem by translating training data from a related source domain to a novel target domain, but typically assume that a one-to-one translation is possible.
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