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Adapting a trained model to perform satisfactorily on continually changing testing domains/environments is an important and challenging task.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L. J. Li, K. Li, and L. Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
Mark Everingham, Luc Gool, Christopher K. Williams, John Winn, and Andrew Zisserman · 2010
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Domain-adversarial neural networks
Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, and Mario Marchand · 2014
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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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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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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Mask R-CNN
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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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 · 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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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua Dillon, Balaji Lakshminarayanan, and Jasper Snoek · 2019
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Snapshot distillation: Teacher-student optimization in one generation
Chenglin Yang, Lingxi Xie, Chi Su, and Alan L Yuille · 2019
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Revisit knowledge distillation: a teacher-free framework
Li Yuan, Francis EH Tay, Guilin Li, Tao Wang, and Jiashi Feng · 2019
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
Cited alongside, same era.
Universal source-free domain adaptation
Jogendra Nath Kundu, Naveen Venkat, R Venkatesh Babu, et al · 2020
Cited alongside, same era.
Model adaptation: Unsupervised domain adaptation without source data
Rui Li, Qianfen Jiao, Wenming Cao, Hau-San Wong, and Si Wu · 2020
Cited alongside, same era.
Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation
Jian Liang, Dapeng Hu, and Jiashi Feng · 2020
Cited alongside, same era.
Self-distillation amplifies regularization in hilbert space
Hossein Mobahi, Mehrdad Farajtabar, and Peter Bartlett · 2020
Cited alongside, same era.
Improving robustness against common corruptions by covariate shift adaptation
Generalized source-free domain adaptation
Shiqi Yang, Yaxing Wang, Joost Van De Weijer, Luis Herranz, and Shangling Jui · 2021
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Parameter-free online test-time adaptation
Malik Boudiaf, Romain Mueller, Ismail Ben Ayed, and Luca Bertinetto · 2022
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Contrastive test-time adaptation
Dian Chen, Dequan Wang, Trevor Darrell, and Sayna Ebrahimi · 2022
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Xcon: Learning with experts for fine-grained category discovery
Yixin Fei, Zhongkai Zhao, Siwei Yang, and Bingchen Zhao · 2022
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Decorate the newcomers: Visual domain prompt for continual test time adaptation
Yulu Gan, Xianzheng Ma, Yihang Lou, Yan Bai, Renrui Zhang, Nian Shi, and Lin Luo · 2022
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Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, and Matthias Bethge · 2020
Cited alongside, same era.
Test-time training with self-supervision for generalization under distribution shifts
Y. Sun, X. Wang, Z. Liu, J. Miller, A. A. Efros, and M. Hardt · 2020
Cited alongside, same era.
Robustbench: a standardized adversarial robustness benchmark
Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, and Matthias Hein · 2021
Cited alongside, same era.
Few-shot class-incremental learning via relation knowledge distillation
Songlin Dong, Xiaopeng Hong, Xiaoyu Tao, Xinyuan Chang, Xing Wei, and Yihong Gong · 2021
Cited alongside, same era.
Knowledge distillation: A survey
Jianping Gou, Baosheng Yu, Stephen J Maybank, and Dacheng Tao · 2021
Cited alongside, same era.
Autoencoder based self-supervised test-time adaptation for medical image analysis
Yufan He, Aaron Carass, Lianrui Zuo, Blake E Dewey, and Jerry L Prince · 2021
Cited alongside, same era.
Model adaptation: Historical contrastive learning for unsupervised domain adaptation without source data
Jiaxing Huang, Dayan Guan, Aoran Xiao, and Shijian Lu · 2021
Cited alongside, same era.
NOTE: Robust continual test-time adaptation against temporal correlation
Taesik Gong, Jongheon Jeong, Taewon Kim, Yewon Kim, Jinwoo Shin, and Sung-Ju Lee · 2022
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Class-incremental learning by knowledge distillation with adaptive feature consolidation
Minsoo Kang, Jaeyoo Park, and Bohyung Han · 2022
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Maohao Shen, Yuheng Bu, and Gregory Wornell · 2022
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Generalized category discovery
Sagar Vaze, Kai Han, Andrea Vedaldi, and Andrew Zisserman · 2022
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Continual test-time domain adaptation
Qin Wang, Olga Fink, Luc Van Gool, and Dengxin Dai · 2022
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Cross-domain contrastive learning for unsupervised domain adaptation
Rui Wang, Zuxuan Wu, Zejia Weng, Jingjing Chen, Guo-Jun Qi, and Yu-Gang Jiang · 2022
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Attracting and dispersing: A simple approach for source-free domain adaptation
Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, et al · 2022
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Pcl: Proxy-based contrastive learning for domain generalization
Xufeng Yao, Yang Bai, Xinyun Zhang, Yuechen Zhang, Qi Sun, Ran Chen, Ruiyu Li, and Bei Yu · 2022
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Xuejun Zhao, Rafal Stanislawski, Paolo Gardoni, Maciej Sulowicz, Adam Glowacz, Grzegorz Krolczyk, and Zhixiong Li · 2022
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TTN: A domain-shift aware batch normalization in test-time adaptation
Hyesu Lim, Byeonggeun Kim, Jaegul Choo, and Sungha Choi · 2023
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Delta: degradation-free fully test-time adaptation
Bowen Zhao, Chen Chen, and Shu-Tao Xia · 2023
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