A Fourier Transform Framework for Domain Adaptation

arXiv:2403.07798v2 Announce Type: replace
Abstract: By using unsupervised domain adaptation (UDA), knowledge can be transferred from a label-rich source domain to a target domain that contains relevant information but lacks labels. Many existing UDA algorithms suffer from directly using raw images as input, resulting in models that overly focus on redundant information and exhibit poor generalization capability. To address this issue, we attempt to improve the performance of unsupervised domain adaptation by employing the Fourier method (FTF).Specifically, FTF is inspired …

abstract algorithms arxiv cs.cv domain domain adaptation focus fourier framework images information knowledge labels raw type unsupervised