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Federated Learning (FL) has recently emerged as a possible way to tackle the domain shift in real-world Semantic Segmentation (SS) without compromising the private nature of the collected data.
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Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell · 2014
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The cityscapes dataset for semantic urban scene understanding
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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
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Daniel Ramage Brendan McMahan · 2017
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Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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No more discrimination: Cross city adaptation of road scene segmenters
Yi-Hsin Chen, Wei-Yu Chen, Yu-Ting Chen, Bo-Cheng Tsai, Yu-Chiang Frank Wang, and Min Sun · 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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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017
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The mapillary vistas dataset for semantic understanding of street scenes
Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulo, and Peter Kontschieder · 2017
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Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
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Leaf: A benchmark for federated settings
Sebastian Caldas, Sai Meher Karthik Duddu, Peter Wu, Tian Li, Jakub Konečný, H. Brendan McMahan, Virginia Smith, and Ameet Talwalkar · 2018
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Cycada: Cycle-consistent adversarial domain adaptation
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Averaging weights leads to wider optima and better generalization
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Federated optimization in heterogeneous networks
Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, and Virginia Smith · 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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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
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Multi-institutional deep learning modeling without sharing patient data: A feasibility study on brain tumor segmentation
Micah J Sheller, G Anthony Reina, Brandon Edwards, Jason Martin, and Spyridon Bakas · 2018
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Learning to adapt structured output space for semantic segmentation
Y.-H. Tsai, W.-C. Hung, S. Schulter, K. Sohn, M.-H. Yang, and M. Chandraker · 2018
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Unsupervised domain adaptation for semantic segmentation via class-balanced self-training
Yang Zou, Zhiding Yu, BVK Vijaya Kumar, and Jinsong Wang · 2018
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Towards federated learning at scale: System design
Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloe Kiddon, Jakub Konečnỳ, Stefano Mazzocchi, Brendan McMahan, et al · 2019
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Scaffold: Stochastic controlled averaging for federated learning
Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank J Reddi, Sebastian U Stich, and Ananda Theertha Suresh · 2019
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Privacy-preserving federated brain tumour segmentation
Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu, Maximilian Baust, Yan Cheng, Sébastien Ourselin, M. Jorge Cardoso, and Andrew Feng · 2019
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Feddis: Disentangled federated learning for unsupervised brain pathology segmentation
Cosmin I Bercea, Benedikt Wiestler, Daniel Rueckert, and Shadi Albarqouni · 2021
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Cluster-driven graph federated learning over multiple domains
Debora Caldarola, Massimiliano Mancini, Fabio Galasso, Marco Ciccone, Emanuele Rodolà, and Barbara Caputo · 2021
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Twins: Revisiting the design of spatial attention in vision transformers
Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, and Chunhua Shen · 2021
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Unsupervised domain adaptation for semantic image segmentation: a comprehensive survey
Gabriela Csurka, Riccardo Volpi, and Boris Chidlovskii · 2021
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Uncertainty reduction for model adaptation in semantic segmentation
Francois Fleuret et al · 2021
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Constructing self-motivated pyramid curriculums for cross-domain semantic segmentation: A non-adversarial approach
Qing Lian, Fengmao Lv, Lixin Duan, and Boqing Gong · 2019
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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
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IDDA: A large-scale multi-domain dataset for autonomous driving
E. Alberti, A. Tavera, C. Masone, and B. Caputo · 2020
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Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation
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Advances and open problems in federated learning
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Generalize then adapt: Source-free domain adaptive semantic segmentation
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Federated learning on non-iid data silos: An experimental study
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Source-free domain adaptation for semantic segmentation
Yuang Liu, Wei Zhang, and Jun Wang · 2021
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Source-free domain adaptation for semantic segmentation
Yuang Liu, Wei Zhang, and Jun Wang · 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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Are all users treated fairly in federated learning systems?
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Prototype guided federated learning of visual feature representations
Umberto Michieli and Mete Ozay · 2021
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Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
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A survey on federated learning
Chen Zhang, Yu Xie, Hang Bai, Bin Yu, Weihong Li, and Yuan Gao · 2021
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Improving generalization in federated learning by seeking flat minima
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Feddrive: Generalizing federated learning to semantic segmentation in autonomous driving
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Federated learning from only unlabeled data with class-conditional-sharing clients
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SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints
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Federated unsupervised domain adaptation for face recognition
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