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NAM: Non-Adversarial Unsupervised Domain Mapping
[chapter]
2018
Lecture Notes in Computer Science
Several methods were recently proposed for the task of translating images between domains without prior knowledge in the form of correspondences. The existing methods apply adversarial learning to ensure that the distribution of the mapped source domain is indistinguishable from the target domain, which suffers from known stability issues. In addition, most methods rely heavily on "cycle" relationships between the domains, which enforce a one-to-one mapping. In this work, we introduce an
doi:10.1007/978-3-030-01264-9_27
fatcat:br2lqynqdvfmznhyg6pfzcxgym