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Unsupervised domain adaptation (UDA) aims to transfer knowledge learned from a labeled source domain to a different unlabeled target domain.
Semi-supervised learning by entropy minimization
Yves Grandvalet, Yoshua Bengio, et al · 2005
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A kernel method for the two-sample-problem
Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, and Alex Smola · 2006
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Adapting visual category models to new domains
Kate Saenko, Brian Kulis, Mario Fritz, and Trevor Darrell · 2010
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Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee et al · 2013
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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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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael Jordan · 2015
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Deep reconstruction-classification networks for unsupervised domain adaptation
Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, and Wen Li · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
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Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
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Unsupervised pixel-level domain adaptation with generative adversarial networks
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, and Dilip Krishnan · 2017
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Beyond triplet loss: a deep quadruplet network for person re-identification
Weihua Chen, Xiaotang Chen, Jianguo Zhang, and Kaiqi Huang · 2017
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Domain adaptation for visual applications: A comprehensive survey
Gabriela Csurka · 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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Visda: The visual domain adaptation challenge
Xingchao Peng, Ben Usman, Neela Kaushik, Judy Hoffman, Dequan Wang, and Kate Saenko · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Deep hashing network for unsupervised domain adaptation
Hemanth Venkateswara, Jose Eusebio, Shayok Chakraborty, and Sethuraman Panchanathan · 2017
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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Cycada: Cycle-consistent adversarial domain adaptation
Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei Efros, and Trevor Darrell · 2018
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Conditional adversarial domain adaptation
Mingsheng Long, Zhangjie Cao, Jianmin Wang, and Michael I Jordan · 2018
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Maximum classifier discrepancy for unsupervised domain adaptation
Kuniaki Saito, Kohei Watanabe, Yoshitaka Ushiku, and Tatsuya Harada · 2018
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Collaborative and adversarial network for unsupervised domain adaptation
Weichen Zhang, Wanli Ouyang, Wen Li, and Dong Xu · 2018
Cited alongside, same era.
Unsupervised domain adaptation for semantic segmentation via class-balanced self-training
Yang Zou, Zhiding Yu, BVK Kumar, and Jinsong Wang · 2018
Cited alongside, same era.
Domain-specific batch normalization for unsupervised domain adaptation
Woong-Gi Chang, Tackgeun You, Seonguk Seo, Suha Kwak, and Bohyung Han · 2019
Cited alongside, same era.
Transferability vs. discriminability: Batch spectral penalization for adversarial domain adaptation
Xinyang Chen, Sinan Wang, Mingsheng Long, and Jianmin Wang · 2019
Cited alongside, same era.
Pseudo-labeling curriculum for unsupervised domain adaptation
Jaehoon Choi, Minki Jeong, Taekyung Kim, and Changick Kim · 2019
Cited alongside, same era.
Generative pseudo-label refinement for unsupervised domain adaptation
Pietro Morerio, Riccardo Volpi, Ruggero Ragonesi, and Vittorio Murino · 2020
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A survey of unsupervised deep domain adaptation
Garrett Wilson and Diane J Cook · 2020
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Unsupervised multi-class domain adaptation: Theory, algorithms, and practice
Yabin Zhang, Bin Deng, Hui Tang, Lei Zhang, and Kui Jia · 2020
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A review of single-source deep unsupervised visual domain adaptation
Sicheng Zhao, Xiangyu Yue, Shanghang Zhang, Bo Li, Han Zhao, Bichen Wu, Ravi Krishna, Joseph E Gonzalez, Alberto L Sangiovanni-Vincentelli, Sanjit A Seshia, et al · 2020
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Cross-domain gradient discrepancy minimization for unsupervised domain adaptation
Zhekai Du, Jingjing Li, Hongzu Su, Lei Zhu, and Ke Lu · 2021
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Cluster alignment with a teacher for unsupervised domain adaptation
Zhijie Deng, Yucen Luo, and Jun Zhu · 2019
Cited alongside, same era.
Contrastive adaptation network for unsupervised domain adaptation
Guoliang Kang, Lu Jiang, Yi Yang, and Alexander G Hauptmann · 2019
Cited alongside, same era.
Unsupervised domain adaptation based on source-guided discrepancy
Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, and Masashi Sugiyama · 2019
Cited alongside, same era.
Sliced wasserstein discrepancy for unsupervised domain adaptation
Chen-Yu Lee, Tanmay Batra, Mohammad Haris Baig, and Daniel Ulbricht · 2019
Cited alongside, same era.
Neural speech synthesis with transformer network
Naihan Li, Shujie Liu, Yanqing Liu, Sheng Zhao, and Ming Liu · 2019
Cited alongside, same era.
Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
Cited alongside, same era.
Learning to rank proposals for object detection
Zhiyu Tan, Xuecheng Nie, Qi Qian, Nan Li, and Hao Li · 2019
Cited alongside, same era.
Shuting He, Hao Luo, Pichao Wang, Fan Wang, Hao Li, and Wei Jiang · 2021
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Unit: Multimodal multitask learning with a unified transformer
Ronghang Hu and Amanpreet Singh · 2021
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Exploring the quality of gan generated images for person re-identification
Yiqi Jiang, Weihua Chen, Xiuyu Sun, Xiaoyu Shi, Fan Wang, and Hao Li · 2021
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Transformers in vision: A survey
Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, and Mubarak Shah · 2021
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Domain adaptation with auxiliary target domain-oriented classifier
Jian Liang, Dapeng Hu, and Jiashi Feng · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Unsupervised domain adaption of object detectors: A survey
Poojan Oza, Vishwanath A Sindagi, Vibashan VS, and Vishal M Patel · 2021
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Learning accurate entropy model with global reference for image compression
Yichen Qian, Zhiyu Tan, Xiuyu Sun, Ming Lin, Dongyang Li, Zhenhong Sun, Hao Li, and Rong Jin · 2021
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Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Mega-cda: Memory guided attention for category-aware unsupervised domain adaptive object detection
Vibashan VS, Vikram Gupta, Poojan Oza, Vishwanath A Sindagi, and Vishal M Patel · 2021
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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Transformer-based source-free domain adaptation
Guanglei Yang, Hao Tang, Zhun Zhong, Mingli Ding, Ling Shao, Nicu Sebe, and Elisa Ricci · 2021
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Transrppg: Remote photoplethysmography transformer for 3d mask face presentation attack detection
Zitong Yu, Xiaobai Li, Pichao Wang, and Guoying Zhao · 2021
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Rectifying pseudo label learning via uncertainty estimation for domain adaptive semantic segmentation
Zhedong Zheng and Yi Yang · 2021
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Entroformer: A transformer-based entropy model for learned image compression
Yichen Qian, Xiuyu Sun, Ming Lin, Zhiyu Tan, and Rong Jin · 2022
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Ada-nets: Face clustering via adaptive neighbour discovery in the structure space
Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, YuQi Zhang, and Xiuyu Sun · 2022
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Giraffedet: A heavy-neck paradigm for object detection
Junyan Wang Xiuyu Sun Ming Lin Hao Li Yiqi Jiang, Zhiyu Tan · 2022
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