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Deep domain adaption has emerged as a new learning technique to address the lack of massive amounts of labeled data.
Integrating structured biological data by kernel maximum mean discrepancy
K. M. Borgwardt, A. Gretton, M. J. Rasch, H.-P. Kriegel, B. Schölkopf, and A. J. Smola · 2006
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A fast learning algorithm for deep belief nets
G. E. Hinton, S. Osindero, and Y.-W. Teh · 2006
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Learning deep architectures for ai
Y. Bengio · 2009
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Learning to detect unseen object classes by between-class attribute transfer
C. H. Lampert, H. Nickisch, and S. Harmeling · 2009
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Domain adaptation problems: A dasvm classification technique and a circular validation strategy
L. Bruzzone and M. Marconcini · 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
Earlier work this paper cites.
Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol · 2010
Earlier work this paper cites.
Domain adaptation for large-scale sentiment classification: A deep learning approach
X. Glorot, A. Bordes, and Y. Bengio · 2011
Earlier work this paper cites.
Domain adaptation for object recognition: An unsupervised approach
R. Gopalan, R. Li, and R. Chellappa · 2011
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What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
B. Kulis, K. Saenko, and T. Darrell · 2011
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Domain adaptation via transfer component analysis
S. J. Pan, I. W. Tsang, J. T. Kwok, and Q. Yang · 2011
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Heterogeneous domain adaptation using manifold alignment
C. Wang and S. Mahadevan · 2011
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Marginalized denoising autoencoders for domain adaptation
M. Chen, Z. Xu, K. Weinberger, and F. Sha · 2012
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Learning with augmented features for heterogeneous domain adaptation
L. Duan, D. Xu, and I. Tsang · 2012
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Geodesic flow kernel for unsupervised domain adaptation
B. Gong, Y. Shi, F. Sha, and K. Grauman · 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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Dlid: Deep learning for domain adaptation by interpolating between domains
S. Chopra, S. Balakrishnan, and R. Gopalan · 2013
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Selective transfer machine for personalized facial action unit detection
W.-S. Chu, F. De la Torre, and J. F. Cohn · 2013
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Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain adaptation
B. Gong, K. Grauman, and F. Sha · 2013
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One-shot adaptation of supervised deep convolutional models
J. Hoffman, E. Tzeng, J. Donahue, Y. Jia, K. Saenko, and T. Darrell · 2013
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Decaf: A deep convolutional activation feature for generic visual recognition
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell · 2014
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Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
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Domain adaptive neural networks for object recognition
M. Ghifary, W. B. Kleijn, and M. Zhang · 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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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Lsda: Large scale detection through adaptation
J. Hoffman, S. Guadarrama, E. S. Tzeng, R. Hu, J. Donahue, R. Girshick, T. Darrell, and K. Saenko · 2014
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Neural decision forests for semantic image labelling
S. Rota Bulo and P. Kontschieder · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
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Deep domain confusion: Maximizing for domain invariance
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell · 2014
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How transferable are features in deep neural networks?
J. Yosinski, J. Clune, Y. Bengio, and H. Lipson · 2014
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Heterogeneous domain adaptation for multiple classes
J. T. Zhou, I. W. Tsang, S. J. Pan, and M. Tan · 2014
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Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2015
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Unsupervised domain adaptation via representation learning and adaptive classifier learning
M. Gheisari and M. S. Baghshah · 2015
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Domain generalization for object recognition with multi-task autoencoders
M. Ghifary, W. Bastiaan Kleijn, M. Zhang, and D. Balduzzi · 2015
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Fast r-cnn
R. Girshick · 2015
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Distilling the knowledge in a neural network
G. Hinton, O. Vinyals, and J. Dean · 2015
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Deep transfer metric learning
J. Hu, J. Lu, and Y.-P. Tan · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
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Bi-shifting auto-encoder for unsupervised domain adaptation
M. Kan, S. Shan, and X. Chen · 2015
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Deep neural decision forests
P. Kontschieder, M. Fiterau, A. Criminisi, and S. Rota Bulo · 2015
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Generative moment matching networks
Y. Li, K. Swersky, and R. Zemel · 2015
Earlier work this paper cites.
Learning transferable features with deep adaptation networks
M. Long, Y. Cao, J. Wang, and M. Jordan · 2015
Earlier work this paper cites.
Composite sketch recognition via deep network-a transfer learning approach
P. Mittal, M. Vatsa, and R. Singh · 2015
Earlier work this paper cites.
Dash-n: Joint hierarchical domain adaptation and feature learning
H. V. Nguyen, H. T. Ho, V. M. Patel, and R. Chellappa · 2015
Earlier work this paper cites.
Visual domain adaptation: A survey of recent advances
V. M. Patel, R. Gopalan, R. Li, and R. Chellappa · 2015
Earlier work this paper cites.
Subspace alignment based domain adaptation for rcnn detector
A. Raj, V. P. Namboodiri, and T. Tuytelaars · 2015
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Cited alongside, same era.
Weakly supervised localization of novel objects using appearance transfer
M. Rochan and Y. Wang · 2015
Cited alongside, same era.
U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
Transfer learning for visual categorization: A survey
L. Shao, F. Zhu, and X. Li · 2015
Cited alongside, same era.
Weakly-shared deep transfer networks for heterogeneous-domain knowledge propagation
X. Shu, G.-J. Qi, J. Tang, and J. Wang · 2015
Cited alongside, same era.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
Partial transfer learning with selective adversarial networks
Z. Cao, M. Long, J. Wang, and M. I. Jordan · 2017
Later among the works it cites.
Autodial: Automatic domain alignment layers
F. M. Carlucci, L. Porzi, B. Caputo, E. Ricci, and S. R. Bulò · 2017
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Show, adapt and tell: Adversarial training of cross-domain image captioner
T.-H. Chen, Y.-H. Liao, C.-Y. Chuang, W.-T. Hsu, J. Fu, and M. Sun · 2017
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Road: Reality oriented adaptation for semantic segmentation of urban scenes
Y. Chen, W. Li, and L. Van Gool · 2017
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No more discrimination: Cross city adaptation of road scene segmenters
Y.-H. Chen, W.-Y. Chen, Y.-T. Chen, B.-C. Tsai, Y.-C. F. Wang, and M. Sun · 2017
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Cited alongside, same era.
Transitive transfer learning
B. Tan, Y. Song, E. Zhong, and Q. Yang · 2015
Cited alongside, same era.
Adapting deep visuomotor representations with weak pairwise constraints
E. Tzeng, C. Devin, J. Hoffman, C. Finn, P. Abbeel, S. Levine, K. Saenko, and T. Darrell · 2015
Cited alongside, same era.
Simultaneous deep transfer across domains and tasks
E. Tzeng, J. Hoffman, T. Darrell, and K. Saenko · 2015
Cited alongside, same era.
Transfer learning from deep features for remote sensing and poverty mapping
M. Xie, N. Jean, M. Burke, D. Lobell, and S. Ermon · 2015
Cited alongside, same era.
Deep transfer network: Unsupervised domain adaptation
X. Zhang, F. X. Yu, S.-F. Chang, and S. Wang · 2015
Cited alongside, same era.
Supervised representation learning: Transfer learning with deep autoencoders
F. Zhuang, X. Cheng, P. Luo, S. J. Pan, and Q. He · 2015
Cited alongside, same era.
Domain adaptation for visual applications: A comprehensive survey
G. Csurka · 2017
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A survey on heterogeneous transfer learning
O. Day and T. M. Khoshgoftaar · 2017
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W. Deng, L. Zheng, G. Kang, Y. Yang, Q. Ye, and J. Jiao · 2017
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Borrowing treasures from the wealthy: Deep transfer learning through selective joint fine-tuning
W. Ge and Y. Yu · 2017
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Fine-grained recognition in the wild: A multi-task domain adaptation approach
T. Gebru, J. Hoffman, and L. Fei-Fei · 2017
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Associative domain adaptation
P. Haeusser, T. Frerix, A. Mordvintsev, and D. Cremers · 2017
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Sspp-dan: Deep domain adaptation network for face recognition with single sample per person
S. Hong, W. Im, J. Ryu, and H. S. Yang · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
X. Huang and S. Belongie · 2017
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Learning to discover cross-domain relations with generative adversarial networks
T. Kim, M. Cha, H. Kim, J. Lee, and J. Kim · 2017
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Deeper, broader and artier domain generalization
D. Li, Y. Yang, Y.-Z. Song, and T. M. Hospedales · 2017
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Demystifying neural style transfer
Y. Li, N. Wang, J. Liu, and X. Hou · 2017
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A survey of deep neural network architectures and their applications
W. Liu, Z. Wang, X. Liu, N. Zeng, Y. Liu, and F. E. Alsaadi · 2017
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When unsupervised domain adaptation meets tensor representations
H. Lu, L. Zhang, Z. Cao, W. Wei, K. Xian, C. Shen, and A. van den Hengel · 2017
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Few-shot adversarial domain adaptation
S. Motiian, Q. Jones, S. Iranmanesh, and G. Doretto · 2017
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Unified deep supervised domain adaptation and generalization
S. Motiian, M. Piccirilli, D. A. Adjeroh, and G. Doretto · 2017
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Hashing in the zero shot framework with domain adaptation
S. Pachori, A. Deshpande, and S. Raman · 2017
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Zero-shot deep domain adaptation
K.-C. Peng, Z. Wu, and J. Ernst · 2017
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Synthetic to real adaptation with deep generative correlation alignment networks
X. Peng and K. Saenko · 2017
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Learning multiple visual domains with residual adapters
S.-A. Rebuffi, H. Bilen, and A. Vedaldi · 2017
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Asymmetric tri-training for unsupervised domain adaptation
K. Saito, Y. Ushiku, and T. Harada · 2017
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Maximum classifier discrepancy for unsupervised domain adaptation
K. Saito, K. Watanabe, Y. Ushiku, and T. Harada · 2017
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Learning from synthetic data: Addressing domain shift for semantic segmentation
S. Sankaranarayanan, Y. Balaji, A. Jain, S. N. Lim, and R. Chellappa · 2017
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Wasserstein distance guided representation learning for domain adaptation
J. Shen, Y. Qu, W. Zhang, and Y. Yu · 2017
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Unsupervised domain adaptation for face recognition in unlabeled videos
K. Sohn, S. Liu, G. Zhong, X. Yu, M.-H. Yang, and M. Chandraker · 2017
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Distant domain transfer learning
B. Tan, Y. Zhang, S. J. Pan, and Q. Yang · 2017
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Adversarial domain separation and adaptation
J.-C. Tsai and J.-T. Chien · 2017
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Adversarial discriminative domain adaptation
E. Tzeng, J. Hoffman, K. Saenko, and T. Darrell · 2017
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D. Ulyanov, A. Vedaldi, and V. Lempitsky · 2017
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Adversarial feature augmentation for unsupervised domain adaptation
R. Volpi, P. Morerio, S. Savarese, and V. Murino · 2017
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High-quality facial photo-sketch synthesis using multi-adversarial networks
L. Wang, V. A. Sindagi, and V. M. Patel · 2017
Later among the works it cites.
Detecting smiles of young children via deep transfer learning
Y. Xia, D. Huang, and Y. Wang · 2017
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Mind the class weight bias: Weighted maximum mean discrepancy for unsupervised domain adaptation
H. Yan, Y. Ding, P. Li, Q. Wang, Y. Xu, and W. Zuo · 2017
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Dualgan: Unsupervised dual learning for image-to-image translation
Z. Yi, H. Zhang, P. T. Gong, et al · 2017
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Central moment discrepancy (cmd) for domain-invariant representation learning
W. Zellinger, T. Grubinger, E. Lughofer, T. Natschläger, and S. Saminger-Platz · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
H. Zhang, T. Xu, H. Li, S. Zhang, X. Huang, X. Wang, and D. Metaxas · 2017
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Transfer learning for cross-dataset recognition: A survey
J. Zhang, W. Li, and P. Ogunbona · 2017
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Deep object recognition across domains based on adaptive extreme learning machine
L. Zhang, Z. He, and Y. Liu · 2017
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Curriculum domain adaptation for semantic segmentation of urban scenes
Y. Zhang, P. David, and B. Gong · 2017
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Dual learning for cross-domain image captioning
W. Zhao, W. Xu, M. Yang, J. Ye, Z. Zhao, Y. Feng, and Y. Qiao · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
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Domain adaptive faster r-cnn for object detection in the wild
Y. Chen, W. Li, C. Sakaridis, D. Dai, and L. Van Gool · 2018
Closest in time.
Cross-domain weakly-supervised object detection through progressive domain adaptation
N. Inoue, R. Furuta, T. Yamasaki, and K. Aizawa · 2018
Closest in time.
Importance weighted adversarial nets for partial domain adaptation
J. Zhang, Z. Ding, W. Li, and P. Ogunbona · 2018
Closest in time.