Search Results for author: Tianshuo Zhang

Found 2 papers, 1 papers with code

Safe Self-Refinement for Transformer-based Domain Adaptation

1 code implementation CVPR 2022 Tao Sun, Cheng Lu, Tianshuo Zhang, Haibin Ling

Unsupervised Domain Adaptation (UDA) aims to leverage a label-rich source domain to solve tasks on a related unlabeled target domain.

Unsupervised Domain Adaptation

Shuffle Augmentation of Features from Unlabeled Data for Unsupervised Domain Adaptation

no code implementations28 Jan 2022 Changwei Xu, Jianfei Yang, Haoran Tang, Han Zou, Cheng Lu, Tianshuo Zhang

Unsupervised Domain Adaptation (UDA), a branch of transfer learning where labels for target samples are unavailable, has been widely researched and developed in recent years with the help of adversarially trained models.

Unsupervised Domain Adaptation

Cannot find the paper you are looking for? You can Submit a new open access paper.