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We propose a novel Generalized Zero-Shot learning (GZSL) method that is agnostic to both unseen images and unseen semantic vectors during training.
Describing objects by their attributes
A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth · 2009
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Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
D. Koller and N. Friedman · 2009
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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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Devise: A deep visual-semantic embedding model
A. Frome, G. S. Corrado, J. Shlens, S. Bengio, J. Dean, T. Mikolov, et al · 2013
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Zero-shot learning by convex combination of semantic embeddings
M. Norouzi, T. Mikolov, S. Bengio, Y. Singer, J. Shlens, A. Frome, G. S. Corrado, and J. Dean · 2013
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Zero-shot learning via visual abstraction
S. Antol, C. L. Zitnick, and D. Parikh · 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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ImageNet Large Scale Visual Recognition Challenge, 2014
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 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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Sparse local embeddings for extreme multi-label classification
K. Bhatia, H. Jain, P. Kar, M. Varma, and P. Jain · 2015
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Zero-shot learning via semantic similarity embedding
Z. Zhang and V. Saligrama · 2015
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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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An empirical study and analysis of generalized zero-shot learning for object recognition in the wild
W.-L. Chao, S. Changpinyo, B. Gong, and F. Sha · 2016
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Sun database: Exploring a large collection of scene categories
J. Xiao, K. A. Ehinger, J. Hays, A. Torralba, and A. Oliva · 2016
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Semantic autoencoder for zero-shot learning
E. Kodirov, T. Xiang, and S. Gong · 2017
Preserving semantic relations for zero-shot learning
Y. Annadani and S. Biswas · 2018
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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 · 2018
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Learning class prototypes via structure alignment for zero-shot recognition
H. Jiang, R. Wang, S. Shan, and X. Chen · 2018
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Generalized zero-shot learning via synthesized examples
V. Kumar Verma, G. Arora, A. Mishra, and P. Rai · 2018
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Multi-label zero-shot learning with structured knowledge graphs
C.-W. Lee, W. Fang, C.-K. Yeh, and Y.-C. Frank Wang · 2018
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Discriminative learning of latent features for zero-shot recognition
Y. Li, J. Zhang, J. Zhang, and K. Huang · 2018
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Zero-shot recognition using dual visual-semantic mapping paths
Y. Li, D. Wang, H. Hu, Y. Lin, and Y. Zhuang · 2017
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A simple exponential family framework for zero-shot learning
V. K. Verma and P. Rai · 2017
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Learning a deep embedding model for zero-shot learning
L. Zhang, T. Xiang, and S. Gong · 2017
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Learning multi-attention convolutional neural network for fine-grained image recognition
H. Zheng, J. Fu, T. Mei, and J. Luo · 2017
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Zero-shot recognition via semantic embeddings and knowledge graphs
X. Wang, Y. Ye, and A. Gupta · 2018
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Zero-shot learning-a comprehensive evaluation of the good, the bad and the ugly
Y. Xian, C. H. Lampert, B. Schiele, and Z. Akata · 2018
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Feature generating networks for zero-shot learning
Y. Xian, T. Lorenz, B. Schiele, and Z. Akata · 2018
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A generative adversarial approach for zero-shot learning from noisy texts
Y. Zhu, M. Elhoseiny, B. Liu, X. Peng, and A. Elgammal · 2018
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