Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping

Unsupervised domain mapping aims to learn a function to translate domain X to Y by a function GXY in the absence of paired examples. Finding the optimal GXY without paired data is an ill-posed problem, so appropriate constraints are required to obtain reasonable solutions... (read more)

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