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Simulation-to-real domain adaptation for semantic segmentation has been actively studied for various applications such as autonomous driving.
Cross-domain video concept detection using adaptive svms
Jun Yang, Rong Yan, and Alexander G Hauptmann · 2007
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Domain adaptation from multiple sources via auxiliary classifiers
Lixin Duan, Ivor W Tsang, Dong Xu, and Tat-Seng Chua · 2009
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An empirical analysis of domain adaptation algorithms for genomic sequence analysis
Gabriele Schweikert, Gunnar Rätsch, Christian Widmer, and Bernhard Schölkopf · 2009
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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
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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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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2010
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Unbiased look at dataset bias
Antonio Torralba and Alexei A Efros · 2011
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Domain adaptation for large-scale sentiment classification: A deep learning approach
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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A two-stage weighting framework for multi-source domain adaptation
Qian Sun, Rita Chattopadhyay, Sethuraman Panchanathan, and Jieping Ye · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Robust visual domain adaptation with low-rank reconstruction
I-Hong Jhuo, Dong Liu, DT Lee, and Shih-Fu Chang · 2012
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Exploiting web images for event recognition in consumer videos: A multiple source domain adaptation approach
Lixin Duan, Dong Xu, and Shih-Fu Chang · 2012
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Multisource domain adaptation and its application to early detection of fatigue
Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, and Jieping Ye · 2012
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Domain adaptation from multiple sources: A domain-dependent regularization approach
Lixin Duan, Dong Xu, and Ivor Wai-Hung Tsang · 2012
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Multi-source transfer learning with multi-view adaboost
Zhijie Xu and Shiliang Sun · 2012
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Non-linear domain adaptation with boosting
Carlos J Becker, Christos M Christoudias, and Pascal Fua · 2013
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Bayesian multi-source domain adaptation
Shi-Liang Sun and Hong-Lei Shi · 2013
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Unsupervised adaptation across domain shifts by generating intermediate data representations
Raghuraman Gopalan, Ruonan Li, and Rama Chellappa · 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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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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Semantic image segmentation via deep parsing network
Ziwei Liu, Xiaoxiao Li, Ping Luo, Chen-Change Loy, and Xiaoou Tang · 2015
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Conditional random fields as recurrent neural networks
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, and Philip HS Torr · 2015
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Visual domain adaptation: A survey of recent advances
Vishal M Patel, Raghuraman Gopalan, Ruonan Li, and Rama Chellappa · 2015
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The variational fair autoencoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, and Richard Zemel · 2015
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Domain generalization for object recognition with multi-task autoencoders
Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, and David Balduzzi · 2015
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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael Jordan · 2015
Cited alongside, same era.
A survey of multi-source domain adaptation
Shiliang Sun, Honglei Shi, and Yuanbin Wu · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
Cited alongside, same era.
Efficient piecewise training of deep structured models for semantic segmentation
Visda: The visual domain adaptation challenge
Xingchao Peng, Ben Usman, Neela Kaushik, Judy Hoffman, Dequan Wang, and Kate Saenko · 2017
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Virtual-to-real: learning to control in visual semantic segmentation
Zhang-Wei Hong, Yu-Ming Chen, Hsuan-Kung Yang, Shih-Yang Su, Tzu-Yun Shann, Yi-Hsiang Chang, Brian Hsi-Lin Ho, Chih-Chieh Tu, Tsu-Ching Hsiao, Hsin-Wei Hsiao, et al · 2018
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Understanding convolution for semantic segmentation
Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell · 2018
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A lidar point cloud generator: from a virtual world to autonomous driving
Xiangyu Yue, Bichen Wu, Sanjit A Seshia, Kurt Keutzer, and Alberto L Sangiovanni-Vincentelli · 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 A Efros, and Trevor Darrell · 2018
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Guosheng Lin, Chunhua Shen, Anton Van Den Hengel, and Ian Reid · 2016
Cited alongside, same era.
Multi-scale context aggregation by dilated convolutions
Fisher Yu and Vladlen Koltun · 2016
Cited alongside, same era.
The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
Cited alongside, same era.
Playing for data: Ground truth from computer games
Stephan R Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun · 2016
Cited alongside, same era.
The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio M Lopez · 2016
Cited alongside, same era.
Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
Cited alongside, same era.
Coupled generative adversarial networks
Ming-Yu Liu and Oncel Tuzel · 2016
Cited alongside, same era.
Emotiongan: unsupervised domain adaptation for learning discrete probability distributions of image emotions
Sicheng Zhao, Xin Zhao, Guiguang Ding, and Kurt Keutzer · 2018
Later among the works it cites.
From source to target and back: symmetric bi-directional adaptive gan
Paolo Russo, Fabio M Carlucci, Tatiana Tommasi, and Barbara Caputo · 2018
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Generate to adapt: Aligning domains using generative adversarial networks
Swami Sankaranarayanan, Yogesh Balaji, Carlos D Castillo, and Rama Chellappa · 2018
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Duplex generative adversarial network for unsupervised domain adaptation
Lanqing Hu, Meina Kan, Shiguang Shan, and Xilin Chen · 2018
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Road: Reality oriented adaptation for semantic segmentation of urban scenes
Yuhua Chen, Wen Li, and Luc Van Gool · 2018
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Learning from synthetic data: Addressing domain shift for semantic segmentation
Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain, Ser Nam Lim, and Rama Chellappa · 2018
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Fully convolutional adaptation networks for semantic segmentation
Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, and Tao Mei · 2018
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Domain stylization: A strong, simple baseline for synthetic to real image domain adaptation
Aysegul Dundar, Ming-Yu Liu, Ting-Chun Wang, John Zedlewski, and Jan Kautz · 2018
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Penalizing top performers: Conservative loss for semantic segmentation adaptation
Xinge Zhu, Hui Zhou, Ceyuan Yang, Jianping Shi, and Dahua Lin · 2018
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Dcan: Dual channel-wise alignment networks for unsupervised scene adaptation
Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gokhan Uzunbas, Tom Goldstein, Ser Nam Lim, and Larry S Davis · 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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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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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2018
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Learning to adapt structured output space for semantic segmentation
Yi-Hsuan Tsai, Wei-Chih Hung, Samuel Schulter, Kihyuk Sohn, Ming-Hsuan Yang, and Manmohan Chandraker · 2018
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Bdd100k: A diverse driving video database with scalable annotation tooling
Fisher Yu, Wenqi Xian, Yingying Chen, Fangchen Liu, Mike Liao, Vashisht Madhavan, and Trevor Darrell · 2018
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Semantic understanding of scenes through the ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Tete Xiao, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2019
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Squeezesegv2: Improved model structure and unsupervised domain adaptation for road-object segmentation from a lidar point cloud
Bichen Wu, Xuanyu Zhou, Sicheng Zhao, Xiangyu Yue, and Kurt Keutzer · 2019
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Cycleemotiongan: Emotional semantic consistency preserved cyclegan for adapting image emotions
Sicheng Zhao, Chuang Lin, Pengfei Xu, Sendong Zhao, Yuchen Guo, Ravi Krishna, Guiguang Ding, and Kurt Keutzer · 2019
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Domain randomization and pyramid consistency: Simulation-to-real generalization without accessing target domain data
Xiangyu Yue, Yang Zhang, Sicheng Zhao, Alberto Sangiovanni-Vincentelli, Kurt Keutzer, and Boqing Gong · 2019
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Learning to learn without forgetting by maximizing transfer and minimizing interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, and Gerald Tesauro · 2019
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