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Conventional zero-shot learning (ZSL) methods generally learn an embedding, e.g., visual-semantic mapping, to handle the unseen visual samples via an indirect manner.
Automated flower classification over a large number of classes
M-E. Nilsback and A. Zisserman · 2008
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Learning to detect unseen object classes by between-class attribute transfer
Christoph H Lampert, Hannes Nickisch, and Stefan Harmeling · 2009
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The caltech-ucsd birds-200-2011 dataset
Catherine Wah, Steve Branson, Peter Welinder, Pietro Perona, and Serge Belongie · 2011
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Sun attribute database: Discovering, annotating, and recognizing scene attributes
Genevieve Patterson and James Hays · 2012
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Devise: A deep visual-semantic embedding model
Andrea Frome, Greg S Corrado, Jon Shlens, Samy Bengio, Jeff Dean, Tomas Mikolov, et al · 2013
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Zero-shot learning by convex combination of semantic embeddings
Mohammad Norouzi, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg S Corrado, and Jeffrey Dean · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Attribute-based classification for zero-shot visual object categorization
Christoph H Lampert, Hannes Nickisch, and Stefan Harmeling · 2014
Earlier work this paper cites.
Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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Evaluation of output embeddings for fine-grained image classification
Zeynep Akata, Scott Reed, Daniel Walter, Honglak Lee, and Bernt Schiele · 2015
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Unsupervised domain adaptation for zero-shot learning
Elyor Kodirov, Tao Xiang, Zhenyong Fu, and Shaogang Gong · 2015
Earlier work this paper cites.
Predicting deep zero-shot convolutional neural networks using textual descriptions
Jimmy Lei Ba, Kevin Swersky, Sanja Fidler, et al · 2015
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An embarrassingly simple approach to zero-shot learning
Bernardino Romera-Paredes and Philip Torr · 2015
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Ridge regression, hubness, and zero-shot learning
Yutaro Shigeto, Ikumi Suzuki, Kazuo Hara, Masashi Shimbo, and Yuji Matsumoto · 2015
Earlier work this paper cites.
Zero-shot learning via semantic similarity embedding
Ziming Zhang and Venkatesh Saligrama · 2015
Cited alongside, same era.
Label-embedding for image classification
Zeynep Akata, Florent Perronnin, Zaid Harchaoui, and Cordelia Schmid · 2016
Cited alongside, same era.
Synthesized classifiers for zero-shot learning
Soravit Changpinyo, Wei-Lun Chao, Boqing Gong, and Fei Sha · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Learning deep representations of fine-grained visual descriptions
Scott Reed, Zeynep Akata, Honglak Lee, and Bernt Schiele · 2016
Cited alongside, same era.
Zero-shot learning via joint latent similarity embedding
Ziming Zhang and Venkatesh Saligrama · 2016
Cited alongside, same era.
Zero-shot learning-the good, the bad and the ugly
Yongqin Xian, Bernt Schiele, and Zeynep Akata · 2017
Later among the works it cites.
Zero-shot classification with discriminative semantic representation learning
Meng Ye and Yuhong Guo · 2017
Later among the works it cites.
Learning a deep embedding model for zero-shot learning
Li Zhang, Tao Xiang, Shaogang Gong, et al · 2017
Later among the works it cites.
Generative zero-shot learning via low-rank embedded semantic dictionary
Zhengming Ding, Ming Shao, and Yun Fu · 2018
Later among the works it cites.
Heterogeneous domain adaptation through progressive alignment
Jingjing Li, Ke Lu, Zi Huang, Lei Zhu, and Heng Tao Shen · 2018
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Transfer independently together: A generalized framework for domain adaptation
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
Cited alongside, same era.
Low-rank embedded ensemble semantic dictionary for zero-shot learning
Zhengming Ding, Ming Shao, and Yun Fu · 2017
Cited alongside, same era.
Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
Cited alongside, same era.
Learning discriminative latent attributes for zero-shot classification
Huajie Jiang, Ruiping Wang, Shiguang Shan, Yi Yang, and Xilin Chen · 2017
Cited alongside, same era.
Semantic autoencoder for zero-shot learning
Elyor Kodirov, Tao Xiang, and Shaogang Gong · 2017
Cited alongside, same era.
Two birds one stone: on both cold-start and long-tail recommendation
Jingjing Li, Ke Lu, Zi Huang, and Heng Tao Shen · 2017
Cited alongside, same era.
Jingjing Li, Ke Lu, Zi Huang, Lei Zhu, and Heng Tao Shen · 2018
Later among the works it cites.
I read, i saw, i tell: Texts assisted fine-grained visual classification
Jingjing Li, Lei Zhu, Zi Huang, Ke Lu, and Jidong Zhao · 2018
Later among the works it cites.
Towards affordable semantic searching: Zero-shot. retrieval via dominant attributes
Yang Long, Li Liu, Yuming Shen, Ling Shao, and J Song · 2018
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A generative model for zero shot learning using conditional variational autoencoders
Ashish Mishra, M Reddy, Anurag Mittal, and Hema A Murthy · 2018
Later among the works it cites.
Generalized zero-shot learning via synthesized examples
V Kumar Verma, Gundeep Arora, Ashish Mishra, and Piyush Rai · 2018
Later among the works it cites.
Feature generating networks for zero-shot learning
Yongqin Xian, Tobias Lorenz, Bernt Schiele, and Zeynep Akata · 2018
Later among the works it cites.
A generative adversarial approach for zero-shot learning from noisy texts
Yizhe Zhu, Mohamed Elhoseiny, Bingchen Liu, Xi Peng, and Ahmed Elgammal · 2018
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From zero-shot learning to cold-start recommendation
Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, and Zi Huang · 2019
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