Unsupervised Domain Expansion
2 papers with code • 2 benchmarks • 2 datasets
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Benchmarks
These leaderboards are used to track progress in Unsupervised Domain Expansion
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UDE-Office-Home
Most implemented papers
Unsupervised Domain Expansion for Visual Categorization
In this paper we extend UDA by proposing a new task called unsupervised domain expansion (UDE), which aims to adapt a deep model for the target domain with its unlabeled data, meanwhile maintaining the model's performance on the source domain.
Co-Teaching for Unsupervised Domain Adaptation and Expansion
Such sorts of samples are typically in minority in their host domain, so they tend to be overlooked by the domain-specific model, but can be better handled by a model from the other domain.
