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Improving model's generalizability against domain shifts is crucial, especially for safety-critical applications such as autonomous driving.
Integrating structured biological data by kernel maximum mean discrepancy
Karsten M Borgwardt, Arthur Gretton, Malte J Rasch, Hans-Peter Kriegel, Bernhard Schölkopf, and Alex J Smola · 2006
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Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, 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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Adapting visual category models to new domains
Kate Saenko, Brian Kulis, Mario Fritz, and Trevor Darrell · 2010
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Undoing the damage of dataset bias
Aditya Khosla, Tinghui Zhou, Tomasz Malisiewicz, Alexei A Efros, and Antonio Torralba · 2012
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias
Chen Fang, Ye Xu, and Daniel N Rockmore · 2013
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Visualizing and understanding convolutional networks
Matthew D Zeiler and Rob Fergus · 2014
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 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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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Scatter component analysis: A unified framework for domain adaptation and domain generalization
Muhammad Ghifary, David Balduzzi, W Bastiaan Kleijn, and Mengjie Zhang · 2016
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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
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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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Domain separation networks
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, and Dumitru Erhan · 2016
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Unsupervised domain adaptation with residual transfer networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I Jordan · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
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Revisiting batch normalization for practical domain adaptation
Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, and Xiaodi Hou · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Instance normalization: The missing ingredient for fast stylization
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2016
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Playing for data: Ground truth from computer games
Stephan R Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun · 2016
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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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Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 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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Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A Adjeroh, and Gianfranco Doretto · 2017
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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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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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Curriculum domain adaptation for semantic segmentation of urban scenes
Yang Zhang, Philip David, and Boqing Gong · 2017
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Correlation alignment for unsupervised domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?
Matthew Johnson-Roberson, Charles Barto, Rounak Mehta, Sharath Nittur Sridhar, Karl Rosaen, and Ram Vasudevan · 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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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Semantic foggy scene understanding with synthetic data
Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2018
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Imagenet-trained cnns are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos, Patricia Rubisch, Claudio Michaelis, Matthias Bethge, Felix A Wichmann, and Wieland Brendel · 2018
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2018
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Learning robust representations by projecting superficial statistics out
Haohan Wang, Zexue He, Zachary C Lipton, and Eric P Xing · 2018
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Metareg: Towards domain generalization using meta-regularization
Yogesh Balaji, Swami Sankaranarayanan, and Rama Chellappa · 2018
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Deepjdot: Deep joint distribution optimal transport for unsupervised domain adaptation
Bharath Bhushan Damodaran, Benjamin Kellenberger, Rémi Flamary, Devis Tuia, and Nicolas Courty · 2018
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Domain adaptive faster r-cnn for object detection in the wild
Yuhua Chen, Wen Li, Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2018
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Cross-domain weakly-supervised object detection through progressive domain adaptation
Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki, and Kiyoharu Aizawa · 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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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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Unsupervised domain adaptation for semantic segmentation via class-balanced self-training
Yang Zou, Zhiding Yu, BVK Kumar, and Jinsong Wang · 2018
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Domain generalization with adversarial feature learning
Haoliang Li, Sinno Jialin Pan, Shiqi Wang, and Alex C Kot · 2018
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Deep adversarial attention alignment for unsupervised domain adaptation: the benefit of target expectation maximization
Guoliang Kang, Liang Zheng, Yan Yan, and Yi Yang · 2018
Cited alongside, same era.
Co-regularized alignment for unsupervised domain adaptation
Abhishek Kumar, Prasanna Sattigeri, Kahini Wadhawan, Leonid Karlinsky, Rogerio Feris, Bill Freeman, and Gregory Wornell · 2018
Cited alongside, same era.
Minimal-entropy correlation alignment for unsupervised deep domain adaptation
Pietro Morerio, Jacopo Cavazza, and Vittorio Murino · 2018
Cited alongside, same era.
Detach and adapt: Learning cross-domain disentangled deep representation
Yen-Cheng Liu, Yu-Ying Yeh, Tzu-Chien Fu, Sheng-De Wang, Wei-Chen Chiu, and Yu-Chiang Frank Wang · 2018
Cited alongside, same era.
Robust place categorization with deep domain generalization
Massimiliano Mancini, Samuel Rota Bulo, Barbara Caputo, and Elisa Ricci · 2018
Cited alongside, same era.
Robust and generalizable visual representation learning via random convolutions
Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, and Marc Niethammer · 2020
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Frustratingly simple domain generalization via image stylization
Nathan Somavarapu, Chih-Yao Ma, and Zsolt Kira · 2020
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Ms-net: multi-site network for improving prostate segmentation with heterogeneous mri data
Quande Liu, Qi Dou, Lequan Yu, and Pheng Ann Heng · 2020
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Learning to optimize domain specific normalization for domain generalization
Seonguk Seo, Yumin Suh, Dongwan Kim, Geeho Kim, Jongwoo Han, and Bohyung Han · 2020
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Tent: Fully test-time adaptation by entropy minimization
Dequan Wang, Evan Shelhamer, Shaoteng Liu, Bruno Olshausen, and Trevor Darrell · 2020
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Two at once: Enhancing learning and generalization capacities via ibn-net
Xingang Pan, Ping Luo, Jianping Shi, and Xiaoou Tang · 2018
Cited alongside, same era.
Group normalization
Yuxin Wu and Kaiming He · 2018
Cited alongside, same era.
Hallucinating agnostic images to generalize across domains
Fabio Maria Carlucci, Paolo Russo, Tatiana Tommasi, and Barbara Caputo · 2019
Cited alongside, same era.
Dlow: Domain flow for adaptation and generalization
Rui Gong, Wen Li, Yuhua Chen, and Luc Van Gool · 2019
Cited alongside, same era.
Feature-critic networks for heterogeneous domain generalization
Yiying Li, Yongxin Yang, Wei Zhou, and Timothy Hospedales · 2019
Cited alongside, same era.
Episodic training for domain generalization
Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M Hospedales · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Universal source-free domain adaptation
Jogendra Nath Kundu, Naveen Venkat, R Venkatesh Babu, et al · 2020
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Test-time training with self-supervision for generalization under distribution shifts
Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei Efros, and Moritz Hardt · 2020
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Improving the generalizability of convolutional neural network-based segmentation on cmr images
Chen Chen, Wenjia Bai, Rhodri H Davies, Anish N Bhuva, Charlotte H Manisty, Joao B Augusto, James C Moon, Nay Aung, Aaron M Lee, Mihir M Sanghvi, et al · 2020
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Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation
Ling Zhang, Xiaosong Wang, Dong Yang, Thomas Sanford, Stephanie Harmon, Baris Turkbey, Bradford J Wood, Holger Roth, Andriy Myronenko, Daguang Xu, et al · 2020
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Learning to generate novel domains for domain generalization
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, and Tao Xiang · 2020
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Deep domain-adversarial image generation for domain generalisation
Kaiyang Zhou, Yongxin Yang, Timothy Hospedales, and Tao Xiang · 2020
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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
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Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2020
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Cross-domain detection via graph-induced prototype alignment
Minghao Xu, Hang Wang, Bingbing Ni, Qi Tian, and Wenjun Zhang · 2020
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Every pixel matters: Center-aware feature alignment for domain adaptive object detector
Cheng-Chun Hsu, Yi-Hsuan Tsai, Yen-Yu Lin, and Ming-Hsuan Yang · 2020
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Acdc: The adverse conditions dataset with correspondences for semantic driving scene understanding
Christos Sakaridis, Dengxin Dai, and Luc Van Gool · 2021
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Domain generalization using causal matching
Divyat Mahajan, Shruti Tople, and Amit Sharma · 2021
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Style normalization and restitution for domain generalization and adaptation
Xin Jin, Cuiling Lan, Wenjun Zeng, and Zhibo Chen · 2021
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Learning to generalize unseen domains via memory-based multi-source meta-learning for person re-identification
Yuyang Zhao, Zhun Zhong, Fengxiang Yang, Zhiming Luo, Yaojin Lin, Shaozi Li, and Nicu Sebe · 2021
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Robustnet: Improving domain generalization in urban-scene segmentation via instance selective whitening
Sungha Choi, Sanghun Jung, Huiwon Yun, Joanne T Kim, Seungryong Kim, and Jaegul Choo · 2021
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Domain-invariant disentangled network for generalizable object detection
Chuang Lin, Zehuan Yuan, Sicheng Zhao, Peize Sun, Changhu Wang, and Jianfei Cai · 2021
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Robust object detection via instance-level temporal cycle confusion
Xin Wang, Thomas E Huang, Benlin Liu, Fisher Yu, Xiaolong Wang, Joseph E Gonzalez, and Trevor Darrell · 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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Seeking similarities over differences: Similarity-based domain alignment for adaptive object detection
Farzaneh Rezaeianaran, Rakshith Shetty, Rahaf Aljundi, Daniel Olmeda Reino, Shanshan Zhang, and Bernt Schiele · 2021
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Domain adaptive ensemble learning
Kaiyang Zhou, Yongxin Yang, Yu Qiao, and Tao Xiang · 2021
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Toalign: Task-oriented alignment for unsupervised domain adaptation
Guoqiang Wei, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, and Zhibo Chen · 2021
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Metaalign: Coordinating domain alignment and classification for unsupervised domain adaptation
Guoqiang Wei, Cuiling Lan, Wenjun Zeng, and Zhibo Chen · 2021
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Self-supervised learning across domains
Silvia Bucci, Antonio D’Innocente, Yujun Liao, Fabio Maria Carlucci, Barbara Caputo, and Tatiana Tommasi · 2021
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Prototypical cross-domain self-supervised learning for few-shot unsupervised domain adaptation
Xiangyu Yue, Zangwei Zheng, Shanghang Zhang, Yang Gao, Trevor Darrell, Kurt Keutzer, and Alberto Sangiovanni Vincentelli · 2021
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Rethinking domain generalization baselines
Francesco Cappio Borlino, Antonio D’Innocente, and Tatiana Tommasi · 2021
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Semi-supervised domain generalization with stochastic stylematch
Kaiyang Zhou, Chen Change Loy, and Ziwei Liu · 2021
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Consistency regularization with high-dimensional nonadversarial source-guided perturbation for unsupervised domain adaptation in segmentation
Kaihong Wang, Chenhongyi Yang, and Margrit Betke · 2021
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Rethinking" batch" in batchnorm
Yuxin Wu and Justin Johnson · 2021
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Meta batch-instance normalization for generalizable person re-identification
Seokeon Choi, Taekyung Kim, Minki Jeong, Hyoungseob Park, and Changick Kim · 2021
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Adversarially adaptive normalization for single domain generalization
Xinjie Fan, Qifei Wang, Junjie Ke, Feng Yang, Boqing Gong, and Mingyuan Zhou · 2021
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Memo: Test time robustness via adaptation and augmentation
Marvin Mengxin Zhang, Sergey Levine, and Chelsea Finn · 2021
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Test-time classifier adjustment module for model-agnostic domain generalization
Yusuke Iwasawa and Yutaka Matsuo · 2021
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Learning to diversify for single domain generalization
Zijian Wang, Yadan Luo, Ruihong Qiu, Zi Huang, and Mahsa Baktashmotlagh · 2021
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Crossnorm and selfnorm for generalization under distribution shifts
Zhiqiang Tang, Yunhe Gao, Yi Zhu, Zhi Zhang, Mu Li, and Dimitris N Metaxas · 2021
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Permuted adain: reducing the bias towards global statistics in image classification
Oren Nuriel, Sagie Benaim, and Lior Wolf · 2021
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A simple feature augmentation for domain generalization
Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, and Timothy M Hospedales · 2021
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Adversarial feature augmentation and normalization for visual recognition
Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Zhangyang Wang, and Jingjing Liu · 2021
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Rethinking and improving the robustness of image style transfer
Pei Wang, Yijun Li, and Nuno Vasconcelos · 2021
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Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation
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Continual test-time domain adaptation
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Semantic-aware domain generalized segmentation
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Feature-based style randomization for domain generalization
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