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Domain generalisation aims to promote the learning of domain-invariant features while suppressing domain-specific features, so that a model can generalise better to previously unseen target domains.
Gradient-based learning applied to document recognition
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Rapid object detection using a boosted cascade of simple features
P. Viola and M. Jones · 2001
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A new metric for probability distributions
D. Endres and J. Schindelin · 2003
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Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
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Object detection with discriminatively trained part-based models
P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan · 2009
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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
M. Everingham, L. Van Gool, C. Williams, J. Winn, and A. Zisserman · 2010
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A survey on transfer learning
S. J. Pan and Q. Yang · 2010
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Adapting visual category models to new domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
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Causal inference using the algorithmic Markov condition
D. Janzing and B. Schölkopf · 2010
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Generalizing from several related classification tasks to a new unlabeled sample
G. Blanchard, G. Lee, and C. Scott · 2011
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A unifying view on dataset shift in classification
J. G. Moreno-Torres, T. Raeder, R. Alaiz-Rodríguez, N. V. Chawla, and F. Herrera · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Undoing the damage of dataset bias
A. Khosla, T. Zhou, T. Malisiewicz, A. A. Efros, and A. Torralba · 2012
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On causal and anticausal learning
B. Schölkopf, D. Janzing, J. Peters, E. Sgouritsa, K. Zhang, and J. Mooij · 2012
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Domain generalization via invariant feature representation
K. Muandet, D. Balduzzi, and B. Schölkopf · 2013
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Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias
C. Fang, Y. Xu, and D. N. Rockmore · 2013
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Microsoft COCO: Common objects in context
T-Y. Lin et al · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Exploiting low-rank structure from latent domains for domain generalization
Z. Xu, W. Li, L. Niu, and D. Xu · 2014
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Generative adversarial networks
I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Fast R-CNN
R. Girshick · 2015
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Domain generalization for object recognition with multi-task autoencoders
M. Ghifary, W. B. Kleijn, M. Zhang, and D. Balduzzi · 2015
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SSD: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C-Y. Fu, and A. C. Berg · 2016
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Faster R-CNN: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2016
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R-FCN: Object detection via region-based fully convolutional networks
J. Dai, Y. Li, K. He, and J. Sun · 2016
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You only look once: Unified, real-time object detection
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
M. Noroozi and P. Favaro · 2016
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Deep multi-task representation learning: A tensor factorisation approach
Y. Yang and T. M. Hospedales · 2016
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Domain-adversarial training of neural networks
Y. Ganin et al · 2016
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Scatter component analysis: A unified framework for domain adaptation and domain generalization
M. Ghifary, D. Balduzzi, W. B. Kleijn, and M. Zhang · 2016
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The Cityscapes dataset for semantic urban scene understanding
M. Cordts et al · 2016
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Feature pyramid networks for object detection
T-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie · 2017
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Plant identification using deep neural networks via optimization of transfer learning parameters
M. M. Ghazi, B. Yanikoglu, and E. Aptoula · 2017
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Domain randomization for transferring deep neural networks from simulation to the real world
J. Tobin, R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel · 2017
Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture
P. Bosilj, E. Aptoula, T. Duckett, and G. Cielniak · 2020
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A decade survey of transfer learning (2010–2020)
S. Niu, Y. Liu, J. Wang, and H. Song · 2020
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Self-supervised visual feature learning with deep neural networks: A survey
L. Jing and Y. Tian · 2020
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Domain generalization for medical imaging classification with linear-dependency regularization
H. Li, Y. Wang, R. Wan, S. Wang, T-Q. Li, and A. Kot · 2020
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Diva: Domain invariant variational autoencoders
M. Ilse, J. M. Tomczak, C. Louizos, and M. Welling · 2020
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Metanorm: Learning to normalize few-shot batches across domains
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Cited alongside, same era.
Deeper, broader and artier domain generalization
D. Li, Y. Yang, Y-Z. Song, and T. M. Hospedales · 2017
Cited alongside, same era.
Model-agnostic meta-learning for fast adaptation of deep networks
C. Finn, P. Abbeel, and S. Levine · 2017
Cited alongside, same era.
Domain adaptive Faster R-CNN for object detection in the wild
Y. Chen, W. Li, C. Sakaridis, D. Dai, and L. Van Gool · 2018
Cited alongside, same era.
Yolov3: An incremental improvement
J. Redmon and A. Farhadi · 2018
Cited alongside, same era.
Generalizing across domains via cross-gradient training
S. Shankar, V. Piratla, S. Chakrabarti, S. Chaudhuri, P. Jyothi, and S. Sarawagi · 2018
Cited alongside, same era.
Semantic foggy scene understanding with synthetic data
C. Sakaridis, D. Dai, and L. Van Gool · 2018
Cited alongside, same era.
Y. Du, X. Zhen, L. Shao, and C. Snoek · 2020
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Learning to generate novel domains for domain generalization
K. Zhou, Y. Yang, T. M. Hospedales, and T. Xiang · 2020
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Single-side domain generalization for face anti-spoofing
Y. Jia, J. Zhang, S. Shan, and X. Chen · 2020
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Domain generalization via entropy regularization
S. Zhao, M. Gong, T. Liu, H. Fu, and D. Tao · 2020
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Domain generalization via multidomain discriminant analysis
S. Hu, K. Zhang, Z. Chen, and L. Chan · 2020
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Domain generalization using a mixture of multiple latent domains
T. Matsuura and T. Harada · 2020
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Bdd100k: A diverse driving dataset for heterogeneous multitask learning
F. Yu, H. Chen, X. Wang, W. Xian, Y. Chen, F. Liu, V. Madhavan, and T. Darrell · 2020
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Domain generalization: A survey
K. Zhou, Z. Liu, Y. Qiao, T. Xiang, and C. C. Loy · 2021
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Wilds: A benchmark of in-the-wild distribution shifts
P. W. Koh et al · 2021
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Domain-invariant disentangled network for generalizable object detection
C. Lin, Z. Yuan, S. Zhao, P. Sun, C. Wang, and J. Cai · 2021
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A deep multitask semisupervised learning approach for chlorophyll-a retrieval from remote sensing images
M. Ilteralp, S. Ariman, and E. Aptoula · 2021
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Domain generalization using causal matching
D. Mahajan, S. Tople, and A. Sharma · 2021
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ACDC: The adverse conditions dataset with correspondences for semantic driving scene understanding
C. Sakaridis, D. Dai, and L. Van Gool · 2021
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Global wheat head detection 2021: an improved dataset for benchmarking wheat head detection methods
E. David et al · 2021
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Global wheat head dataset 2021, July 2021
E. David · 2021
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DESTR: Object detection with split transformer
L. He and S. Todorovic · 2022
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Learning multiple dense prediction tasks from partially annotated data
W-H. Li, X. Liu, and H. Bilen · 2022
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Gradient matching for domain generalization
S. Yuge et al · 2022
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Towards efficient use of multi-scale features in transformer-based object detectors
G. Zhang, Z. Luo, Z. Tian, J. Zhang, X. Zhang, and S. Lu · 2023
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Feature shrinkage pyramid for camouflaged object detection with transformers
Z. Huang, H. Dai, T-Z. Xiang, S. Wang, H-X. Chen, J. Qin, and H. Xiong · 2023
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J. Hindel, N. Gosala, K. Bregler, and A. Valada · 2023
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SSMD-UNet: semi-supervised multi-task decoders network for diabetic retinopathy segmentation
Z. Ullah, M. Usman, S. Latif, A. Khan, and J. Gwak · 2023
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Achieving domain generalization for underwater object detection by domain mixup and contrastive learning
Y. Chen, P. Song, H. Liu, L. Dai, X. Zhang, R. Ding, and S. Li · 2023
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