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Zero-Shot Learning (ZSL) is achieved via aligning the semantic relationships between the global image feature vector and the corresponding class semantic descriptions.
Term-weighting approaches in automatic text retrieval
G. Salton and C. Buckley · 1987
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The caltech-ucsd birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean · 2013
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Zero-shot learning through cross-modal transfer
R. Socher, M. Ganjoo, C. D. Manning, and A. Ng · 2013
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Multiple object recognition with visual attention
J. Ba, V. Mnih, and K. Kavukcuoglu · 2014
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Attribute-based classification for zero-shot visual object categorization
C. H. Lampert, H. Nickisch, and S. Harmeling · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Evaluation of output embeddings for fine-grained image classification
Z. Akata, S. Reed, D. Walter, H. Lee, and B. Schiele · 2015
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Transductive multi-view zero-shot learning
Y. Fu, T. M. Hospedales, T. Xiang, and S. Gong · 2015
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Building a bird recognition app and large scale dataset with citizen scientists: The fine print in fine-grained dataset collection
G. V. Horn, S. Branson, R. Farrell, S. Haber, J. Barry, P. Ipeirotis, P. Perona, and S. Belongie · 2015
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An embarrassingly simple approach to zero-shot learning
B. Romera-Paredes and P. Torr · 2015
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Ridge regression, hubness, and zero-shot learning
Y. Shigeto, I. Suzuki, K. Hara, M. Shimbo, and Y. Matsumoto · 2015
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Multi-cue zero-shot learning with strong supervision
Z. Akata, M. Malinowski, M. Fritz, and B. Schiele · 2016
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Label-embedding for image classification
Z. Akata, F. Perronnin, Z. Harchaoui, and C. Schmid · 2016
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Synthesized classifiers for zero-shot learning
S. Changpinyo, W.-L. Chao, B. Gong, and F. Sha · 2016
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Semi-supervised vocabulary-informed learning
Y. Fu and L. Sigal · 2016
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Less is more: zero-shot learning from online textual documents with noise suppression
R. Qiao, L. Liu, C. Shen, and A. van den Hengel · 2016
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Ask, attend and answer: Exploring question-guided spatial attention for visual question answering
H. Xu and K. Saenko · 2016
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Zero-shot learning by generating pseudo feature representations
J. Lu, J. Li, Z. Yan, and C. Zhang · 2017
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A generative model for zero shot learning using conditional variational autoencoders
A. Mishra, M. Reddy, A. Mittal, and H. A. Murthy · 2017
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Semantically consistent regularization for zero-shot recognition
P. Morgado and N. Vasconcelos · 2017
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Areas of attention for image captioning
M. Pedersoli, T. Lucas, C. Schmid, and J. Verbeek · 2017
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Matrix tri-factorization with manifold regularizations for zero-shot learning
X. Xu, F. Shen, Y. Yang, D. Zhang, H. T. Shen, and J. Song · 2017
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Stacked attention networks for image question answering
Z. Yang, X. He, J. Gao, L. Deng, and A. Smola · 2016
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Image captioning with semantic attention
Q. You, H. Jin, Z. Wang, C. Fang, and J. Luo · 2016
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Zero-shot learning via joint latent similarity embedding
Z. Zhang and V. Saligrama · 2016
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Zero-shot visual recognition using semantics-preserving adversarial embedding network
L. Chen, H. Zhang, J. Xiao, W. Liu, and S.-F. Chang · 2017
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Write a classifier: Predicting visual classifiers from unstructured text
M. Elhoseiny, A. Elgammal, and B. Saleh · 2017
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Link the head to the “beak”: Zero shot learning from noisy text description at part precision
M. Elhoseiny, Y. Zhu, H. Zhang, and A. Elgammal · 2017
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Multi-level attention networks for visual question answering
D. Yu, J. Fu, T. Mei, and Y. Rui · 2017
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Zero-shot learning via latent space encoding
Y. Yu, Z. Ji, J. Guo, and Z. Zhongfei · 2017
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Transductive zero-shot learning with a self-training dictionary approach
Y. Yu, Z. Ji, X. Li, J. Guo, Z. Zhang, H. Ling, and F. Wu · 2017
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Learning a deep embedding model for zero-shot learning
L. Zhang, T. Xiang, S. Gong, et al · 2017
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Zero-shot learning posed as a missing data problem
B. Zhao, B. Wu, T. Wu, and Y. Wang · 2017
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Learning to compare: Relation network for few-shot learning
F. Sung, Y. Yang, L. Zhang, T. Xiang, P. H. Torr, and T. M. Hospedales · 2018
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Zero-shot learning via class-conditioned deep generative models
W. Wang, Y. Pu, V. K. Verma, K. Fan, Y. Zhang, C. Chen, P. Rai, and L. Carin · 2018
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Imagine it for me: Generative adversarial approach for zero-shot learning from noisy texts
Y. Zhu, M. Elhoseiny, B. Liu, and A. Elgammal · 2018
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