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| Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation 会议论文
, USA, 2019
作者: Jian Liang ; Ran He; Zhenan Sun; Tieniu Tan
 浏览 |  Adobe PDF(607Kb) |  收藏 | 浏览/下载：308/84 | 提交时间：2019/06/10
Domain Adaptation |
| Geometry Guided Adversarial Facial Expression Synthesis 会议论文
, Seoul, Korea, 2018.10.22-2018.10.26
作者: Lingxiao Song; Zhihe Lu; Ran He; Zhenan Sun; Tieniu Tan
浏览 | Adobe PDF(9351Kb) | 收藏 | 浏览/下载：369/116 | 提交时间：2019/04/29
Facial Expression Synthesis Generative Adversarial Networks Unpaired Image-to-image Transformation |
| Coupled Deep Learning for Heterogeneous Face Recognition 会议论文
, New Orleans, Louisiana, USA, February 2–7, 2018
作者: Xiang Wu; Lingxiao Song; Ran He; Tieniu Tan
浏览 | Adobe PDF(391Kb) | 收藏 | 浏览/下载：326/86 | 提交时间：2018/01/04 |
| Deep Supervised Discrete Hashing 会议论文
, Long Beach, America, 2017-12
作者: Qi Li; Zhenan Sun; Ran He; Tieniu Tan
浏览 | Adobe PDF(265Kb) | 收藏 | 浏览/下载：375/108 | 提交时间：2018/01/03 |
| Principal Affinity based Cross-Modal Retrieval 会议论文
Proc. Asian Conference on Pattern Recognition, Kuala Lumpur, Malaysia, 2015
作者: Jian Liang; Dong Cao; Ran He(赫然); Zhenan Sun; Tieniu Tan
浏览 | Adobe PDF(138Kb) | 收藏 | 浏览/下载：287/105 | 提交时间：2017/02/25
Cross-modal |
| Adaptive Multi-view Clustering via Cross Trace Lasso 会议论文
Proc. Asian Conference on Pattern Recognition, Kuala Lumpur, Malaysia, 2015
作者: Dong Wang; Ran He(赫然); Liang Wang; Tieniu Tan
浏览 | Adobe PDF(248Kb) | 收藏 | 浏览/下载：295/108 | 提交时间：2017/02/25 |
| Multi-view Clustering via Structured Low-Rank Representation 会议论文
Proc. ACM International Conference on Information and Knowledge Management, Melbourne, Australia, 2015
作者: Dong Wang; Qiyue Yin; Ran He(赫然); Liang Wang; Tieniu Tan
浏览 | Adobe PDF(218Kb) | 收藏 | 浏览/下载：331/131 | 提交时间：2017/02/25 |
| Group-Invariant Cross-Modal Subspace Learning 会议论文
Proc. International Joint Conference on Artificial Intelligence, New York, USA, 2016
作者: Jian Liang; Ran He; Zhenan Sun; Tieniu Tan
浏览 | Adobe PDF(904Kb) | 收藏 | 浏览/下载：352/141 | 提交时间：2017/02/25
Unsupervised Cross-modal Subspace Learning |
