Unsupervised Domain Adaptation for Segmentation with Black-box Source Model

no code implementations • 16 Aug 2022 • Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing, C. -C. Jay Kuo, Georges El Fakhri, Jonghye Woo

Unsupervised domain adaptation (UDA) has been widely used to transfer knowledge from a labeled source domain to an unlabeled target domain to counter the difficulty of labeling in a new domain.

Knowledge Distillation Segmentation +1

Deep Unsupervised Domain Adaptation: A Review of Recent Advances and Perspectives

no code implementations • 15 Aug 2022 • Xiaofeng Liu, Chaehwa Yoo, Fangxu Xing, Hyejin Oh, Georges El Fakhri, Je-Won Kang, Jonghye Woo

Unsupervised domain adaptation (UDA) is proposed to counter this, by leveraging both labeled source domain data and unlabeled target domain data to carry out various tasks in the target domain.

Domain Generalization Out-of-Distribution Detection +3