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Together with the recent advances in semantic segmentation, many domain adaptation methods have been proposed to overcome the domain gap between training and deployment environments.
Isolation forest
Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou · 2008
Earlier work this paper cites.
Semantic object classes in video: A high-definition ground truth database
Gabriel J. Brostow, Julien Fauqueur, and Roberto Cipolla · 2009
Earlier work this paper cites.
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.
The pascal visual object classes (voc) challenge
Mark Everingham, Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
Earlier work this paper cites.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Earlier work this paper cites.
Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
Earlier work this paper cites.
The role of context for object detection and semantic segmentation in the wild
Roozbeh Mottaghi, Xianjie Chen, Xiaobai Liu, Nam-Gyu Cho, Sanja Fidler Seong-Whan Lee, Raquel Urtasun, and Alan Yuille · 2014
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
Long Jonathan, Shelhamer Evan, and Darrell Trevor · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
Earlier work this paper cites.
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
Earlier work this paper cites.
Virtual worlds as proxy for multi-object tracking analysis
A Gaidon, Q Wang, Y Cabon, and E Vig · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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 egmentation of urban scenes
German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, and Antonio opez · 2016
Cited alongside, same era.
Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2017
Cited alongside, same era.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
Cited alongside, same era.
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
Later among the works it cites.
Conditional generative adversarial network for structured domain adaptation
Weixiang Hong, Zhenzhen Wang, Ming Yang, and Junsong Yuan · 2018
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Effective use of synthetic data for urban scene semantic segmentation
Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, and Jose M Alvarez · 2018
Later among the works it cites.
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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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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Yi-Hsin Chen, Wei-Yu Chen, Yu-Ting Chen, Bo-Cheng Tsai, Yu-Chiang Frank Wang, and Min Sun · 2017
Cited alongside, same era.
Slanted stixels: Representing san francisco’s steepest streets
Daniel Hernandez-Juarez, Lukas Schneider, Antonio Espinosa, David Vazquez, Antonio M. Lopez, Uwe Franke, Marc Pollefeys, and Juan Carlos Moure · 2017
Cited alongside, same era.
The mapillary vistas dataset for semantic understanding of street scenes
Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulò, and Peter Kontschieder · 2017
Cited alongside, same era.
Full-resolution residual networks for semantic segmentation in street scenes
Tobias Pohlen, Alexander Hermans, Markus Mathias, and Bastian Leibe · 2017
Cited alongside, same era.
Curriculum domain adaptation for semantic segmentation of urban scenes
Yang Zhang, Philip David, and Boqing Gong · 2017
Cited alongside, same era.
Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
Cited alongside, same era.
Wilddash-creating hazard-aware benchmarks
Oliver Zendel, Katrin Honauer, Markus Murschitz, Daniel Steininger, and Gustavo Fernandez Dominguez · 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.
Ccnet: Criss-cross attention for semantic segmentation
Zilong Huang, Xinggang Wang, Lichao Huang, Chang Huang, Yunchao Wei, and Wenyu Liu · 2019
Later among the works it cites.
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan L Yuille, and Li Fei-Fei · 2019
Later among the works it cites.
Taking a closer look at domain shift: Category-level adversaries for semantics consistent domain adaptation
Yawei Luo, Liang Zheng, Tao Guan, Junqing Yu, and Yi Yang · 2019
Later among the works it cites.
Confidence regularized self-training
Yang Zou, Zhiding Yu, Xiaofeng Liu, BVK Kumar, and Jinsong Wang · 2019
Later among the works it cites.
Bdd100k: A diverse driving dataset for heterogeneous multitask learning
Fisher Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, and Trevor Darrell · 2020
Later among the works it cites.