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Unsupervised domain adaptation methods traditionally assume that all source categories are present in the target domain.
Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2005
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Caltech-256 object category dataset
Gregory Griffin, Alex Holub, and Pietro Perona · 2007
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Adapting visual category models to new domains
Kate Saenko, Brian Kulis, Mario Fritz, and Trevor Darrell · 2010
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2014
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Deep domain confusion: Maximizing for domain invariance
Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell · 2014
Earlier work this paper cites.
Unsupervised visual representation learning by context prediction
Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
Earlier work this paper cites.
Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael I Jordan · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Revisiting batch normalization for practical domain adaptation
Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, and Xiaodi Hou · 2016
Earlier work this paper cites.
Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
Cited alongside, same era.
Learning transferrable representations for unsupervised domain adaptation
Ozan Sener, Hyun Oh Song, Ashutosh Saxena, and Silvio Savarese · 2016
Cited alongside, same era.
Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
Cited alongside, same era.
Open set domain adaptation
Pau Panareda Busto and Juergen Gall · 2017
Cited alongside, same era.
Autodial: Automatic domain alignment layers
Fabio Maria Cariucci, Lorenzo Porzi, Barbara Caputo, Elisa Ricci, and Samuel Rota Bulò · 2017
Cited alongside, same era.
Associative domain adaptation
Philip Haeusser, Thomas Frerix, Alexander Mordvintsev, and Daniel Cremers · 2017
Cited alongside, same era.
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
Later among the works it cites.
Importance weighted adversarial nets for partial domain adaptation
Jing Zhang, Zewei Ding, Wanqing Li, and Philip Ogunbona · 2018
Later among the works it cites.
Unsupervised domain adaptation for semantic segmentation via class-balanced self-training
Yang Zou, Zhiding Yu, BVK Vijaya Kumar, and Jinsong Wang · 2018
Later among the works it cites.
Learning to transfer examples for partial domain adaptation
Zhangjie Cao, Kaichao You, Mingsheng Long, Jianmin Wang, and Qiang Yang · 2019
Later among the works it cites.
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-specific batch normalization for unsupervised domain adaptation
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Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Cited alongside, same era.
Open set domain adaptation
Pau Panareda Busto and Juergen Gall · 2017
Cited alongside, same era.
Automatic differentiation in pytorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
Cited alongside, same era.
Visda: The visual domain adaptation challenge
Xingchao Peng, Ben Usman, Neela Kaushik, Judy Hoffman, Dequan Wang, and Kate Saenko · 2017
Cited alongside, same era.
Asymmetric tri-training for unsupervised domain adaptation
Kuniaki Saito, Yoshitaka Ushiku, and Tatsuya Harada · 2017
Cited alongside, same era.
Deep hashing network for unsupervised domain adaptation
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, and Sethuraman Panchanathan · 2017
Cited alongside, same era.
Woong-Gi Chang, Tackgeun You, Seonguk Seo, Suha Kwak, and Bohyung Han · 2019
Later among the works it cites.
Cluster alignment with a teacher for unsupervised domain adaptation
Zhijie Deng, Yucen Luo, and Jun Zhu · 2019
Later among the works it cites.
Unsupervised deep learning by neighbourhood discovery
Jiabo Huang, Qi Dong, Shaogang Gong, and Xiatian Zhu · 2019
Later among the works it cites.
Separate to adapt: Open set domain adaptation via progressive separation
Hong Liu, Zhangjie Cao, Mingsheng Long, Jianmin Wang, and Qiang Yang · 2019
Later among the works it cites.
Semi-supervised domain adaptation via minimax entropy
Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, and Kate Saenko · 2019
Later among the works it cites.
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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Universal domain adaptation
Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, and Michael I. Jordan · 2019
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Bridging theory and algorithm for domain adaptation
Yuchen Zhang, Tianle Liu, Mingsheng Long, and Michael I Jordan · 2019
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Local aggregation for unsupervised learning of visual embeddings
Chengxu Zhuang, Alex Lin Zhai, and Daniel Yamins · 2019
Later among the works it cites.
Universal source-free domain adaptation
Jogendra Nath Kundu, Naveen Venkat, and R Venkatesh Babu · 2020
Closest in time.
Class-incremental domain adaptation
Jogendra Nath Kundu, Rahul Mysore Venkatesh, Naveen Venkat, Ambareesh Revanur, and R Venkatesh Babu · 2020
Closest in time.