VirDA: Reusing Backbone for Unsupervised Domain Adaptation with Visual Reprogramming

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Abstract
Existing UDA pipelines fine-tune already well-trained backbone parameters for every new source-and-target pair, resulting in the number of training parameters and storage memory growing linearly with each new pair, and also preventing the reuse of these well-trained backbone parameters.
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