Uncertainty-Induced Transferability Representation for Source-Free Unsupervised Domain Adaptation. (arXiv:2208.13986v1 [cs.CV])

Source-free unsupervised domain adaptation (SFUDA) aims to learn a target
domain model using unlabeled target data and the knowledge of a well-trained
source domain model. Most previous SFUDA works focus on inferring semantics of
target data based on the source knowledge. Without measuring the
transferability of the source knowledge, these methods insufficiently exploit
the source knowledge, and fail to identify the reliability of the inferred
target semantics. However, existing transferability measurements require either
source data or target labels, which are …

arxiv domain adaptation free representation uncertainty unsupervised