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FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation. (arXiv:2304.13672v2 [cs.CV] UPDATED)
cs.CV updates on arXiv.org arxiv.org
Medical image segmentation methods normally perform poorly when there is a
domain shift between training and testing data. Unsupervised Domain Adaptation
(UDA) addresses the domain shift problem by training the model using both
labeled data from the source domain and unlabeled data from the target domain.
Source-Free UDA (SFUDA) was recently proposed for UDA without requiring the
source data during the adaptation, due to data privacy or data transmission
issues, which normally adapts the pre-trained deep model in the testing …
arxiv data domain domain adaptation fourier free image medical normally prompting segmentation shift testing training unsupervised visual visual prompting