3 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.CV2019
Virtual Mixup Training for Unsupervised Domain Adaptation
Xudong Mao, Yun Ma, Zhenguo Yang +2
We study the problem of unsupervised domain adaptation which aims to adapt models trained on a labeled source domain to a completely unlabeled target domain. Recently, the cluster…
cs.MM2019★ 3 cited
MMED: A Multi-domain and Multi-modality Event Dataset
Zhenguo Yang, Zehang Lin, Min Cheng +2
In this work, we construct and release a multi-domain and multi-modality event dataset (MMED), containing 25,165 textual news articles collected from hundreds of news media sites (…
cs.IR2019★ 2 cited
Learning Shared Semantic Space with Correlation Alignment for Cross-modal Event Retrieval
Zhenguo Yang, Zehang Lin, Peipei Kang +3
In this paper, we propose to learn shared semantic space with correlation alignment () for multimodal data representations, which aligns nonlinear correlations of multim…