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Zero-shot learning (ZSL) methods have been studied in the unrealistic setting where test data are assumed to come from unseen classes only.
On the algorithmic implementation of multiclass kernel-based vector machines
Crammer, K., Singer, Y.: · 2002
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Shared segmentation of natural scenes using dependent pitman-yor processes
Sudderth, E.B., Jordan, M.I.: · 2008
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Learning to detect unseen object classes by between-class attribute transfer
Lampert, C.H., Nickisch, H., Harmeling, S.: · 2009
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Describing objects by their attributes
Farhadi, A., Endres, I., Hoiem, D., Forsyth, D.: · 2009
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Zero-shot learning with semantic output codes
Palatucci, M., Pomerleau, D., Hinton, G.E., Mitchell, T.M.: · 2009
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Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., Fei-Fei, L.: · 2009
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LoOP: local outlier probabilities
Kriegel, H.P., Kröger, P., Schubert, E., Zimek, A.: · 2009
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Attribute-based transfer learning for object categorization with zero/one training example
Yu, X., Aloimonos, Y.: · 2010
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Optimizing one-shot recognition with micro-set learning
Tang, K.D., Tappen, M.F., Sukthankar, R., Lampert, C.H.: · 2010
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Learning to share visual appearance for multiclass object detection
Salakhutdinov, R., Torralba, A., Tenenbaum, J.: · 2011
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Relative attributes
Parikh, D., Grauman, K.: · 2011
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Evaluating knowledge transfer and zero-shot learning in a large-scale setting
Rohrbach, M., Stark, M., Schiele, B.: · 2011
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The Caltech-UCSD Birds-200-2011 Dataset
Wah, C., Branson, S., Welinder, P., Perona, P., Belongie, S.: · 2011
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Online incremental attribute-based zero-shot learning
Kankuekul, P., Kawewong, A., Tangruamsub, S., Hasegawa, O.: · 2012
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Metric learning for large scale image classification: Generalizing to new classes at near-zero cost
Mensink, T., Verbeek, J., Perronnin, F., Csurka, G.: · 2012
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Efficient estimation of word representations in vector space
Mikolov, T., Chen, K., Corrado, G.S., Dean, J.: · 2013
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Devise: A deep visual-semantic embedding model
Frome, A., Corrado, G.S., Shlens, J., Bengio, S., Dean, J., Ranzato, M., Mikolov, T.: · 2013
Cited alongside, same era.
Zero-shot learning through cross-modal transfer
Socher, R., Ganjoo, M., Manning, C.D., Ng, A.: · 2013
Cited alongside, same era.
Label-embedding for attribute-based classification
Akata, Z., Perronnin, F., Harchaoui, Z., Schmid, C.: · 2013
Cited alongside, same era.
Designing category-level attributes for discriminative visual recognition
Yu, F.X., Cao, L., Feris, R.S., Smith, J.R., Chang, S.F.: · 2013
Cited alongside, same era.
Write a classifier: Zero-shot learning using purely textual descriptions
Elhoseiny, M., Saleh, B., Elgammal, A.: · 2013
Cited alongside, same era.
Toward open set recognition
Scheirer, W.J., de Rezende Rocha, A., Sapkota, A., Boult, T.E.: · 2013
Cited alongside, same era.
The sun attribute database: Beyond categories for deeper scene understanding
Patterson, G., Xu, C., Su, H., Hays, J.: · 2014
Later among the works it cites.
How to transfer? zero-shot object recognition via hierarchical transfer of semantic attributes
Al-Halah, Z., Stiefelhagen, R.: · 2015
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Evaluation of output embeddings for fine-grained image classification
Akata, Z., Reed, S., Walter, D., Lee, H., Schiele, B.: · 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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Zero-shot object recognition by semantic manifold distance
Fu, Z., Xiang, T., Kodirov, E., Gong, S.: · 2015
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Semi-supervised zero-shot classification with label representation learning
Li, X., Guo, Y., Schuurmans, D.: · 2015
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Distributed representations of words and phrases and their compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: · 2013
Cited alongside, same era.
Capturing long-tail distributions of object subcategories
Zhu, X., Anguelov, D., Ramanan, D.: · 2014
Cited alongside, same era.
Costa: Co-occurrence statistics for zero-shot classification
Mensink, T., Gavves, E., Snoek, C.G.: · 2014
Cited alongside, same era.
Zero-shot learning by convex combination of semantic embeddings
Norouzi, M., Mikolov, T., Bengio, S., Singer, Y., Shlens, J., Frome, A., Corrado, G.S., Dean, J.: · 2014
Cited alongside, same era.
Zero-shot recognition with unreliable attributes
Jayaraman, D., Grauman, K.: · 2014
Cited alongside, same era.
Probability models for open set recognition
Scheirer, W.J., Jain, L.P., Boult, T.E.: · 2014
Cited alongside, same era.
Later among the works it cites.
An embarrassingly simple approach to zero-shot learning
Romera-Paredes, B., Torr, P.H.S.: · 2015
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Unsupervised domain adaptation for zero-shot learning
Kodirov, E., Xiang, T., Fu, Z., Gong, S.: · 2015
Later among the works it cites.
Zero-shot learning via semantic similarity embedding
Zhang, Z., Saligrama, V.: · 2015
Later among the works it cites.
Predicting deep zero-shot convolutional neural networks using textual descriptions
Lei Ba, J., Swersky, K., Fidler, S., Salakhutdinov, R.: · 2015
Later among the works it cites.
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: · 2015
Later among the works it cites.
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: · 2015
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Zero-shot learning via joint latent similarity embedding
Zhang, Z., Saligrama, V.: · 2016
Closest in time.
Synthesized classifiers for zero-shot learning
Changpinyo, S., Chao, W.L., Gong, B., Sha, F.: · 2016
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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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