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For domain generalization (DG) and unsupervised domain adaptation (UDA), cross domain feature alignment has been widely explored to pull the feature distributions of different domains in order to learn domain-invariant representations.
A database for handwritten text recognition research
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Gradient-based learning applied to document recognition
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Learning from multiple sources
Koby Crammer, Michael Kearns, and Jennifer Wortman · 2008
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2009
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Domain adaptation with multiple sources
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh, and A R · 2009
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A theory of learning from different domains
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan · 2010
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y. Ng · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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Efficient learning of domain-invariant image representations
Judy Hoffman, Erik Rodner, Jeff Donahue, Trevor Darrell, and Kate Saenko · 2013
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Unsupervised domain adaptation by domain invariant projection
Mahsa Baktashmotlagh, Mehrtash T Harandi, Brian C Lovell, and Mathieu Salzmann · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2014
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Deep domain confusion: Maximizing for domain invariance
Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael I Jordan · 2015
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Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, Ian Goodfellow, and Brendan Frey · 2015
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor S. Lempitsky · 2015
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Unsupervised domain adaptation with residual transfer networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I Jordan · 2016
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Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Scatter component analysis: A unified framework for domain adaptation and domain generalization
Muhammad Ghifary, David Balduzzi, W Bastiaan Kleijn, and Mengjie Zhang · 2016
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Disentangling factors of variation in deep representation using adversarial training
Michael F Mathieu, Junbo Jake Zhao, Junbo Zhao, Aditya Ramesh, Pablo Sprechmann, and Yann LeCun · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Revisiting batch normalization for practical domain adaptation
Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, and Xiaodi Hou · 2016
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Collaborative and adversarial network for unsupervised domain adaptation
Weichen Zhang, Wanli Ouyang, Wen Li, and Dong Xu · 2018
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Adversarial multiple source domain adaptation
Han Zhao, Shanghang Zhang, Guanhang Wu, José MF Moura, Joao P Costeira, and Geoffrey J Gordon · 2018
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A unified feature disentangler for multi-domain image translation and manipulation
Alexander H Liu, Yen-Cheng Liu, Yu-Ying Yeh, and Yu-Chiang Frank Wang · 2018
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Diverse image-to-image translation via disentangled representations
Hsin-Ying Lee, Hung-Yu Tseng, Jia-Bin Huang, Maneesh Singh, and Ming-Hsuan Yang · 2018
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Adversarial multiple source domain adaptation
Han Zhao, Shanghang Zhang, Guanhang Wu, José MF Moura, Joao P Costeira, and Geoffrey J Gordon · 2018
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Algorithms and theory for multiple-source adaptation
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Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
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Deep transfer learning with joint adaptation networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I Jordan · 2017
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Central moment discrepancy (cmd) for domain-invariant representation learning
Werner Zellinger, Thomas Grubinger, Edwin Lughofer, Thomas Natschläger, and Susanne Saminger-Platz · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Unsupervised image-to-image translation networks
Ming-Yu Liu, Thomas Breuel, and Jan Kautz · 2017
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Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A Adjeroh, and Gianfranco Doretto · 2017
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Judy Hoffman, Mehryar Mohri, and Ningshan Zhang · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Cbam: Convolutional block attention module
Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In So Kweon · 2018
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Two at once: Enhancing learning and generalization capacities via ibn-net
Xingang Pan, Ping Luo, Jianping Shi, and Xiaoou Tang · 2018
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Deep cocktail network: Multi-source unsupervised domain adaptation with category shift
Ruijia Xu, Ziliang Chen, Wangmeng Zuo, Junjie Yan, and Liang Lin · 2018
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Visual domain adaptation with manifold embedded distribution alignment
Jindong Wang, Wenjie Feng, Yiqiang Chen, Han Yu, Meiyu Huang, and Philip S Yu · 2018
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Domain generalization by solving jigsaw puzzles
Fabio M Carlucci, Antonio D’Innocente, Silvia Bucci, Barbara Caputo, and Tatiana Tommasi · 2019
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Episodic training for domain generalization
Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M Hospedales · 2019
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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
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Larger norm more transferable: An adaptive feature norm approach for unsupervised domain adaptation
Ruijia Xu, Guanbin Li, Jihan Yang, and Liang Lin · 2019
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Transferable normalization: Towards improving transferability of deep neural networks
Ximei Wang, Ying Jin, Mingsheng Long, Jianmin Wang, and Michael I Jordan · 2019
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Semi-supervised domain adaptation via minimax entropy
Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, and Kate Saenko · 2019
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Dual attention network for scene segmentation
Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang, and Hanqing Lu · 2019
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Adaptive transfer network for cross-domain person re-identification
Jiawei Liu, Zheng-Jun Zha, Di Chen, Richang Hong, and Meng Wang · 2019
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Domain generalization by solving jigsaw puzzles
Fabio M. Carlucci, Antonio D’Innocente, Silvia Bucci, Barbara Caputo, and Tatiana Tommasi · 2019
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Domain adaptive ensemble learning
Kaiyang Zhou, Yongxin Yang, Yu Qiao, and Tao Xiang · 2020
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Style normalization and restitution for generalizable person re-identification
Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen, and Li Zhang · 2020
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