Fetching the paper…
Reading the bibliography…
Zero-shot learning has received increasing interest as a means to alleviate the often prohibitive expense of annotating training data for large scale recognition problems.
Recognition by components - a theory of human image understanding
I. Biederman · 1987
Earlier work this paper cites.
LIBSVM: a library for support vector machines , 2001
Chih-Chung Chang and Chih-Jen Lin · 2001
Earlier work this paper cites.
A kernel method for multi-labelled classification
Andre Elisseeff and Jason Weston · 2001
Earlier work this paper cites.
Modeling the shape of the scene: A holistic representation of the spatial envelope
Aude Oliva and Antonio Torralba · 2001
Earlier work this paper cites.
Zhi-Hua Zhou and Zhao-Qian Chen · 2002
Earlier work this paper cites.
Correlated label propagation with application to multi-label learning
Feng Kang, Rong Jin, and Rahul Sukthankar · 2006
Earlier work this paper cites.
Learning visual attributes
V. Ferrari and A. Zisserman · 2007
Earlier work this paper cites.
Analysis and Evaluation of Visual Information Systems Performance
Michael Grubinger · 2007
Earlier work this paper cites.
Ml-knn: A lazy learning approach to multi-label learning
Min-Ling Zhang and Zhi-Hua Zhou · 2007
Earlier work this paper cites.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Trevor Hastie, Robert Tibshirani, and Jerome Friedman · 2009
Earlier work this paper cites.
Learning to detect unseen object classes by between-class attribute transfer
Christoph H. Lampert, Hannes Nickisch, and Stefan Harmeling · 2009
Earlier work this paper cites.
Zero-shot learning with semantic output codes
Mark Palatucci, Geoffrey Hinton, Dean Pomerleau, and Tom M. Mitchell · 2009
Cited alongside, same era.
Attribute learning for understanding unstructured social activity
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, and Shaogang Gong · 2012
Cited alongside, same era.
Efficient max-margin multi-label classification with applications to zero-shot learning
Bharath Hariharan, S. V. Vishwanathan, and Manik Varma · 2012
Cited alongside, same era.
Improving word representations via global context and multiple word prototypes
Eric H. Huang, Richard Socher, Christopher D. Manning, and Andrew Y. Ng · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
Cited alongside, same era.
Evaluating knowledge transfer and zero-shot learning in a large-scale setting
Transductive multilabel learning via label set propagation
Xiangnan Kong, M.K. Ng, and Zhi-Hua Zhou · 2013
Later among the works it cites.
Attribute-based classification for zero-shot visual object categorization
Christoph H. Lampert, Hannes Nickisch, and Stefan Harmeling · 2013
Later among the works it cites.
Zero-shot learning through cross-modal transfer
Richard Socher, Milind Ganjoo, Hamsa Sridhar, Osbert Bastani, Christopher D. Manning, and Andrew Y. Ng · 2013
Later among the works it cites.
Multi-label classification with unlabeled data: An inductive approach
Le Wu and Min-Ling Zhang · 2013
Later among the works it cites.
A review on multi-label learning algorithms
Min-Ling Zhang and Zhi-Hua Zhou · 2013
Later among the works it cites.
Learning with augmented class by exploiting unlabeled data
Qing Da, Yang Yu, and Zhi-Hua Zhou · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Marcus Rohrbach, Michael Stark, and Bernt Schiele · 2012
Cited alongside, same era.
Augmented attribute representations
Viktoriia Sharmanska, Novi Quadrianto, and Christoph H. Lampert · 2012
Cited alongside, same era.
Cumulative attribute space for age and crowd density estimation
Ke Chen, Shaogang Gong, Tao Xiang, and Chen Chang Loy · 2013
Cited alongside, same era.
Devise: A deep visual-semantic embedding model andrea
Andrea Frome, Greg S. Corrado, Jon Shlens, Samy Bengio, Jeffrey Dean, Marc Aurelio Ranzato, and Tomas Mikolov · 2013
Cited alongside, same era.
Learning multi-modal latent attributes
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, and Shaogang Gong · 2013
Cited alongside, same era.
Transductive multi-view embedding for zero-shot recognition and annotation
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Zhengyong Fu, and Shaogang Gong
Cited in the paper.
Interestingness prediction by robust learning to rank
Yanwei Fu, Timothy M. Hospedales, Tao Xiang, Shaogang Gong, and Yuan Yao
Cited in the paper.
Re-id: Hunting attributes in the wild
Ryan Layne, Timothy M. Hospedales, and Shaogang Gong · 2014
Later among the works it cites.
A pac-bayesian bound for lifelong learning
Anastasia Pentina and Christoph H. Lampert · 2014
Later among the works it cites.
Cnn features off-the-shelf : an astounding baseline for recognition
Ali Sharif Razavian, Josephine Sullivan, and Stefan Carlsson · 2014
Later among the works it cites.
Overfeat: Integrated recognition, localization and detection using convolutional networks
Pierre Sermanet, David Eigen, Xiang Zhang, Michael Mathieu, Rob Fergus, and Yann LeCun · 2014
Later among the works it cites.