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Zero-Shot Learning (ZSL) promises to scale visual recognition by bypassing the conventional model training requirement of annotated examples for every category.
When is ¡°nearest neighbor¡± meaningful?
Beyer, K., Goldstein, J., Ramakrishnan, R., Shaft, U.: · 1999
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Recognizing human actions: A local SVM approach
Schüldt, C., Laptev, I., Caputo, B.: · 2004
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Regularized multi-task learning
Evgeniou, T., Pontil, M.: · 2004
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A kernel method for the two-sample-problem
Gretton, A., Borgwardt, K.M., Rasch, M., Schölkopf, B., Smola, A.J.: · 2006
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Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
Sugiyama, M., Nakajima, S., Kashima, H., Von Bünau, P., Kawanabe, M.: · 2007
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Correcting Sample Selection Bias by Unlabeled Data
Huang, J., Gretton, A., Borgwardt, K.M., Schölkopf, B., Smola, A.J.: · 2007
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Learning to detect unseen object classes by between-class attribute transfer
Lampert, C., Nickisch, H., Harmeling, S.: · 2009
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A Survey on Transfer Learning
Pan, S.J., Yang, Q.: · 2010
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Adapting visual category models to new domains
Saenko, K., Kulis, B., Fritz, M., Darrell, T.: · 2010
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Boosting for Regression Transfer
Pardoe, D., Stone, P.: · 2010
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Modeling temporal structure of decomposable motion segments for activity classification
Niebles, J.C., Chen, C.W., Fei-Fei, L.: · 2010
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Improving the Fisher kernel for large-scale image classification
Perronnin, F., Sánchez, J., Mensink, T.: · 2010
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Human activity analysis: A review
Aggarwal, J.K., Ryoo, M.S.: · 2011
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HMDB: A large video database for human motion recognition
Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.: · 2011
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Recognizing human actions by attributes
Liu, J., Kuipers, B., Savarese, S.: · 2011
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Unbiased look at dataset bias
Torralba, A., Efros, A.A.: · 2011
Cited alongside, same era.
Distributed optimization and statistical learning via the alternating direction method of multipliers
Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: · 2011
Cited alongside, same era.
Ucf101: A dataset of 101 human actions classes from videos in the wild
Soomro, K., Zamir, A., Shah, M.: · 2012
Cited alongside, same era.
Learning Task Grouping and Overlap in Multi-task Learning
Kumar, A., Daum, H., Iii, H.D.: · 2012
Cited alongside, same era.
Zero-shot learning through cross-modal transfer
Socher, R., Ganjoo, M.: · 2013
Cited alongside, same era.
Learning to share latent tasks for action recognition
Zhou, Q., Wang, G., Jia, K., Zhao, Q.: · 2013
Zero-Shot Object Recognition by Semantic Manifold Distance
Fu, Z., Xiang, T., Kodirov, E., Gong, S.: · 2015
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Semantic embedding space for zero-shot action recognition
Xu, X., Hospedales, T., Gong, S.: · 2015
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Transductive Multi-view Zero-Shot Learning
Fu, Y., Hospedales, T.M., Xiang, T., Gong, S.: · 2015
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Improving zero-shot learning by mitigating the hubness problem
Dinu, G., Lazaridou, A., Baroni, M.: · 2015
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Hubness and pollution: Delving into cross-space mapping for zero-shot learning
Lazaridou, A., Dinu, G., Baroni, M.: · 2015
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Reasoning about linguistic regularities in word embeddings using matrix manifolds
Mahadevan, S., Chandar, S.: · 2015
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Cited alongside, same era.
Multi-task sparse learning with beta process prior for action recognition
Yuan, C., Hu, W., Tian, G., Yang, S., Wang, H.: · 2013
Cited alongside, same era.
Latent multitask learning for view-invariant action recognition
Mahasseni, B., Todorovic, S.: · 2013
Cited alongside, same era.
Unsupervised domain adaptation by domain invariant projection
Baktashmotlagh, M., Harandi, M., Lovell, B., Salzmann, M.: · 2013
Cited alongside, same era.
Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., Dean, J.: · 2013
Cited alongside, same era.
VideoStory : A New Multimedia Embedding for Few-Example Recognition and Translation of Events
Habibian, A., Mensink, T., Snoek, C.G.M.: · 2014
Cited alongside, same era.
Importance Weighted Inductive Transfer Learning for Regression
Garcke, J., Vanck, T.: · 2014
Cited alongside, same era.
Unsupervised Domain Adaptation for Zero-Shot Learning
Kodirov, E., Xiang, T., Fu, Z., Gong, S.: · 2015
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A Unified Perspective on Multi-domain and Multi-task Learning
Yang, Y., Hospedales, T.M.: · 2015
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Single/multi-view human action recognition via regularized multi-task learning
Liu, A.A., Xu, N., Su, Y.T., Lin, H., Hao, T., Yang, Z.X.: · 2015
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A robust and efficient video representation for action recognition
Wang, H., Oneata, D., Verbeek, J., Schmid, C., Wang, H., Oneata, D., Verbeek, J., A, C.S.: · 2015
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Zero-shot action recognition by word-vector embedding
Xu, X., Hospedales, T., Gong, S.: · 2015
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An embarrassingly simple approach to zero-shot learning
Romera-paredes, B., Torr, P.H.S.: · 2015
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Recognizing an action using its name: A knowledge-based approach
Gan, C., Yang, Y., Zhu, L., Zhao, D., Zhuang, Y.: · 2016
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Dynamic concept composition for zero-example event detection
Chang, X., Yang, Y., Long, G., Zhang, C., Hauptmann, A.G.: · 2016
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