244 citations · 430 across the 26 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.CV2020
Adversarial Domain Adaptation with Prototype-Based Normalized Output Conditioner
Dapeng Hu, Jian Liang, Qibin Hou +2
In this work, we attempt to address unsupervised domain adaptation by devising simple and compact conditional domain adversarial training methods. We first revisit the simple conca…
cs.CV2020
A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
Jian Liang, Yunbo Wang, Dapeng Hu +2
This work addresses the unsupervised domain adaptation problem, especially in the case of class labels in the target domain being only a subset of those in the source domain. Such…
cs.CV2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Jian Liang, Dapeng Hu, Jiashi Feng
Unsupervised domain adaptation (UDA) aims to leverage the knowledge learned from a labeled source dataset to solve similar tasks in a new unlabeled domain. Prior UDA methods typica…