Evaluating Continual Test-Time Adaptation for Contextual and Semantic Domain Shifts

Imagenet: A large-scale hierarchical image database

J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009

Earlier work this paper cites.

Batch normalization: Accelerating deep network training by reducing internal covariate shift

S. Ioffe and C. Szegedy · 2015

Earlier work this paper cites.

Deep residual learning for image recognition

K. He, X. Zhang, S. Ren, and J. Sun · 2016

Earlier work this paper cites.

Weight normalization: A simple reparameterization to accelerate training of deep neural networks

T. Salimans and D. P. Kingma · 2016

Earlier work this paper cites.

Core50: a new dataset and benchmark for continuous object recognition

V. Lomonaco and D. Maltoni · 2017

Earlier work this paper cites.

Moment matching for multi-source domain adaptation

X. Peng, Q. Bai, X. Xia, Z. Huang, K. Saenko, and B. Wang · 2019

Earlier work this paper cites.

Semi-supervised domain adaptation via minimax entropy

K. Saito, D. Kim, S. Sclaroff, T. Darrell, and K. Saenko · 2019

Earlier work this paper cites.

Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation

J. Liang, D. Hu, and J. Feng · 2020

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Evaluating prediction-time batch normalization for robustness under covariate shift

Z. Nado, S. Padhy, D. Sculley, A. D’Amour, B. Lakshminarayanan, and J. Snoek · 2020

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A survey on domain adaptation theory: learning bounds and theoretical guarantees

I. Redko, E. Morvant, A. Habrard, M. Sebban, and Y. Bennani · 2020

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S. Schneider, E. Rusak, L. Eck, O. Bringmann, W. Brendel, and M. Bethge · 2020

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Test-time training with self-supervision for generalization under distribution shifts

Y. Sun, X. Wang, Z. Liu, J. Miller, A. Efros, and M. Hardt · 2020

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Tent: Fully test-time adaptation by entropy minimization

D. Wang, E. Shelhamer, S. Liu, B. Olshausen, and T. Darrell · 2021

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Test-time batch statistics calibration for covariate shift

F. You, J. Li, and Z. Zhao · 2021

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Contrastive test-time adaptation

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Efficient test-time model adaptation without forgetting

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Learning instance-specific adaptation for cross-domain segmentation

Y. Zou, Z. Zhang, C.-L. Li, H. Zhang, T. Pfister, and J.-B. Huang · 2022

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