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A key topic in classification is the accuracy loss produced when the data distribution in the training (source) domain differs from that in the testing (target) domain.
Histograms of oriented gradients for human detection
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Frustratingly easy domain adaptation
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Depth and appearance for mobile scene analysis
Ess, A., Leibe, B., and Gool, L. V. (2007) · 2007
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Caltech-256 object category dataset
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Cross-domain video concept detection using adaptive SVMs
Yang, J., Yan, R., and Hauptmann, A. (2007) · 2007
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A literature survey on domain adaptation of statistical classifiers
Jiang, J. (2008) · 2008
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Domain adaptation with multiple sources
Mansour, Y., Mohri, M., and Rostamizadeh, A. (2008) · 2008
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A theory of learning from different domains
Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., and Vaughan, J. (2009) · 2009
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Bayesian multitask learning with latent hierarchies
Daumé III, H. (2009) · 2009
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Domain adaptation from multiple sources via auxiliary classifiers
Duan, L., Tsang, I. W., Xu, D., and Chua, T.-S. (2009) · 2009
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Hierarchical bayesian domain adaptation
Finkel, J. and Christopher, D. (2009) · 2009
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A survey on transfer learning
Pan, S. and Yang, Q. (2009) · 2009
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Exploring weakly-labeled web images to improve object classification: a domain adaptation approach
Bergamo, A. and Torresani, L. (2010) · 2010
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Object detection with discriminatively trained part based models
Felzenszwalb, P., Girshick, R., McAllester, D., and Ramanan, D. (2010) · 2010
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Adapting visual category models to new domains
Saenko, K., Hulis, B., Fritz, M., and Darrel, T. (2010) · 2010
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Latent hierarchical structural learning for object detection
Zhu, L., Chen, Y., Yuille, A., and Freeman, W. (2010) · 2010
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Joint 3D estimation of objects and scene layout
A.Geiger, C.Wojek, and R.Urtasun (2011) · 2011
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Tabula rasa: Model transfer for object category detection
Aytar, Y. and Zisserman, A. (2011) · 2011
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Domain adaptation for object recognition: An unsupervised approach
Gopalan, R., Li, R., and Chellappa, R. (2011) · 2011
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Discovering latent domains for multisource domain adaptation
Hoffman, J., Kulis, B., Darrell, T., and Saenko, K. (2012) · 2012
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Unsupervised domain adaptation of virtual and real worlds for pedestrian detection
Vázquez, D., López, A., and Ponsa, D. (2012) · 2012
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Laser-based segment classification using a mixture of bag-of-words
Behley, J., Steinhage, V., and Cremers, A. B. (2013) · 2013
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Reshaping visual datasets for domain adaptation
Gong, B., Grauman, K., and Sha, F. (2013) · 2013
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Efficient learning of domain invariant image representations
Hoffman, J., Rodner, E., Donahue, J., Saenko, K., and Darrell, T. (2013) · 2013
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Domain adaptive classification
Mirrashed, F. and Rastegar, M. (2013) · 2013
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Pedestrian detection: an evaluation of the state of the art
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Learning with augmented features for heterogeneous domain adaptation
Duan, L., Xu, D., and Tsang, I. W. (2012) · 2012
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Discriminatively trained deformable part models, release 5
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Optimization toolkit
Mosek (2013) · 2013
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Subspace interpolation via dictionary learning for unsupervised domain adaptation
Ni, J., Qiu, Q., and Chellappa, R. (2013) · 2013
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Learning kernels for unsupervised domain adaptation with applications to visual object recognition
Gong, B., Grauman, K., and Sha, F. (2014) · 2014
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Asymmetric and category invariant feature transformations for domain adaptation
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Domain adaptation for face recognition: Targetize source domain bridged by common subspace
Kan, M., Wu, J., Shan, S., and Chen, X. (2014) · 2014
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Virtual and real world adaptation for pedestrian detection
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