Transferable semantic augmentation for domain adaptation

S Li, M Xie, K Gong, CH Liu… - Proceedings of the …, 2021 - openaccess.thecvf.com
Abstract Domain adaptation has been widely explored by transferring the knowledge from a
label-rich source domain to a related but unlabeled target domain. Most existing domain …
被引用次数：147 相关文章

Transferable Semantic Augmentation for Domain Adaptation

S Li, M Xie, K Gong, CH Liu, Y Wang… - 2021 IEEE/CVF …, 2021 - computer.org
Abstract Domain adaptation has been widely explored by transferring the knowledge from a
label-rich source domain to a related but unlabeled target domain. Most existing domain …

Transferable Semantic Augmentation for Domain Adaptation

S Li, M Xie, K Gong, CH Liu, Y Wang, W Li - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Abstract Domain adaptation has been widely explored by transferring the knowledge from a
label-rich source domain to a related but unlabeled target domain. Most existing domain …

Transferable Semantic Augmentation for Domain Adaptation

S Li, M Xie, K Gong, CH Liu, Y Wang… - 2021 IEEE/CVF …, 2021 - ieeexplore.ieee.org
Domain adaptation has been widely explored by transferring the knowledge from a label-
rich source domain to a related but unlabeled target domain. Most existing domain …
[PDF] researchgate.net

[PDF][PDF] Transferable Semantic Augmentation for Domain Adaptation

SLMXK Gong, CH Liu, YWW Li - researchgate.net
Abstract Domain adaptation has been widely explored by transferring the knowledge from a
label-rich source domain to a related but unlabeled target domain. Most existing domain …

Transferable Semantic Augmentation for Domain Adaptation

S Li, M Xie, K Gong, CH Liu, Y Wang, W Li - arXiv preprint arXiv …, 2021 - arxiv.org
Domain adaptation has been widely explored by transferring the knowledge from a label-
rich source domain to a related but unlabeled target domain. Most existing domain …