Abstract: Unsupervised domain adaptation(UDA) aims to mitigate the performance drop of models tested on the target domain, due to the domain shift from the target to sources. Most UDA segmentation ...
Abstract: The aim of unsupervised domain adaptation is to leverage the knowledge in a labeled (source) domain to improve a model’s learning performance with an unlabeled (target) domain—the basic ...
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