Fetching the paper…
Reading the bibliography…
Prevalent techniques in zero-shot learning do not generalize well to other related problem scenarios.
One-shot learning of object categories
L. Fei-Fei, R. Fergus, and P. Perona · 2006
Earlier work this paper cites.
Describing objects by their attributes
A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth · 2009
Earlier work this paper cites.
Learning to detect unseen object classes by between-class attribute transfer
C. Lampert, H. Nickisch, and S. Harmeling · 2009
Earlier work this paper cites.
Zero-shot learning with semantic output codes
M. Palatucci, D. Pomerleau, G. E. Hinton, and T. M. Mitchell · 2009
Earlier work this paper cites.
Evaluating knowledge transfer and zero-shot learning in a large-scale setting
M. Rohrbach, M. Stark, and B. Schiele · 2011
Earlier work this paper cites.
The Caltech-UCSD Birds-200-2011 Dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Earlier work this paper cites.
Distance metric learning with eigenvalue optimization
Y. Ying and P. Li · 2012
Earlier work this paper cites.
Label-embedding for attribute-based classification
Z. Akata, F. Perronnin, Z. Harchaoui, and C. Schmid · 2013
Earlier work this paper cites.
Write a classifier: Zero-shot learning using purely textual descriptions
M. Elhoseiny, B. Saleh, and A. Elgammal · 2013
Earlier work this paper cites.
Devise: A deep visual-semantic embedding model
A. Frome, G. S. Corrado, J. Shlens, S. Bengio, J. Dean, M. Ranzato, and T. Mikolov · 2013
Earlier work this paper cites.
Devise: A deep visual-semantic embedding model
A. Frome, G. S. Corrado, J. Shlens, S. Bengio, J. Dean, M. A. Ranzato, and T. Mikolov · 2013
Earlier work this paper cites.
Efficient estimation of word representations in vector space
T. Mikolov, K. Chen, G. Corrado, and J. Dean · 2013
Earlier work this paper cites.
Distributed representations of words and phrases and their compositionality
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean · 2013
Earlier work this paper cites.
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
Earlier work this paper cites.
Learning with hierarchical-deep models
R. Salakhutdinov, J. B. Tenenbaum, and A. Torralba · 2013
Earlier work this paper cites.
Zero-shot learning through cross-modal transfer
R. Socher, M. Ganjoo, C. D. Manning, and A. Ng · 2013
Earlier work this paper cites.
A unified probabilistic approach modeling relationships between attributes and objects
X. Wang and Q. Ji · 2013
Earlier work this paper cites.
Designing category-level attributes for discriminative visual recognition
F. X. Yu, L. Cao, R. S. Feris, J. R. Smith, and S. F. Chang · 2013
Earlier work this paper cites.
Multi-class open set recognition using probability of inclusion
L. P. Jain, W. J. Scheirer, and T. E. Boult · 2014
Cited alongside, same era.
Zero-shot recognition with unreliable attributes
D. Jayaraman and K. Grauman · 2014
Cited alongside, same era.
Attribute-based classification for zero-shot visual object categorization
C. H. Lampert, H. Nickisch, and S. Harmeling · 2014
Cited alongside, same era.
Costa: Co-occurrence statistics for zero-shot classification
T. Mensink, E. Gavves, and C. G. Snoek · 2014
Cited alongside, same era.
The sun attribute database: Beyond categories for deeper scene understanding
G. Patterson, C. Xu, H. Su, and J. Hays · 2014
Cited alongside, same era.
Glove: Global vectors for word representation
J. Pennington, R. Socher, and C. D. Manning · 2014
Cited alongside, same era.
Recovering the missing link: Predicting class-attribute associations for unsupervised zero-shot learning
Z. Al-Halah, M. Tapaswi, and R. Stiefelhagen · 2016
Later among the works it cites.
Towards open set deep networks
A. Bendale and T. E. Boult · 2016
Later among the works it cites.
Synthesized classifiers for zero-shot learning
S. Changpinyo, W.-L. Chao, B. Gong, and F. Sha · 2016
Later among the works it cites.
An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild
W.-L. Chao, B. Changpinyo, Soravitand Gong, and F. Sha · 2016
Later among the works it cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Later among the works it cites.
Improving semantic embedding consistency by metric learning for zero-shot classification
S. H. Maxime Bucher and F. Jurie · 2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Cited alongside, same era.
Accelerating t-sne using tree-based algorithms
L. Van Der Maaten · 2014
Cited alongside, same era.
Evaluation of output embeddings for fine-grained image classification
Z. Akata, S. Reed, D. Walter, H. Lee, and B. Schiele · 2015
Cited alongside, same era.
Active transfer learning with zero-shot priors: Reusing past datasets for future tasks
E. Gavves, T. Mensink, T. Tommasi, C. G. M. Snoek, and T. Tuytelaars · 2015
Cited alongside, same era.
Unsupervised domain adaptation for zero-shot learning
E. Kodirov, T. Xiang, Z. Fu, and S. Gong · 2015
Cited alongside, same era.
Fine-grained recognition without part annotations
J. Krause, H. Jin, J. Yang, and L. Fei-Fei · 2015
Cited alongside, same era.
Later among the works it cites.
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
Later among the works it cites.
Latent embeddings for zero-shot classification
Y. Xian, Z. Akata, G. Sharma, Q. Nguyen, M. Hein, and B. Schiele · 2016
Later among the works it cites.
Fast zero-shot image tagging
Y. Zhang, B. Gong, and M. Shah · 2016
Later among the works it cites.
Zero-shot learning via joint latent similarity embedding
Z. Zhang and V. Saligrama · 2016
Later among the works it cites.
Predicting visual exemplars of unseen classes for zero-shot learning
S. Changpinyo, W.-L. Chao, and F. Sha · 2017
Closest in time.
Zero-shot recognition using dual visual-semantic mapping paths
Y. Li, D. Wang, H. Hu, Y. Lin, and Y. Zhuang · 2017
Closest in time.
Semantically consistent regularization for zero-shot recognition
P. Morgado and N. Vasconcelos · 2017
Closest in time.
Learning robust visual-semantic embeddings
Y. H. Tsai, L. Huang, and R. Salakhutdinov · 2017
Closest in time.
Zero-shot learning - the good, the bad and the ugly
Y. Xian, B. Schiele, and Z. Akata · 2017
Closest in time.
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
Closest in time.
Zero-shot classification with discriminative semantic representation learning
M. Ye and Y. Guo · 2017
Closest in time.