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We introduce a simple yet effective episode-based training framework for zero-shot learning (ZSL), where the learning system requires to recognize unseen classes given only the corresponding class semantics.
Automated flower classification over a large number of classes
Maria-Elena Nilsback and Andrew 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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Label-embedding for attribute-based classification
Zeynep Akata, Florent Perronnin, Zaid Harchaoui, and Cordelia Schmid · 2013
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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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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Autoencoding variational bayes
Diederik P Kingma and Max Welling · 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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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 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
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Learning deep representations of fine-grained visual descriptions
Scott Reed, Zeynep Akata, Honglak Lee, and Bernt Schiele · 2016
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Matching networks for one shot learning
Oriol Vinyals, Charles Blundell, Timothy Lillicrap, Daan Wierstra, et al · 2016
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Latent embeddings for zero-shot classification
Yongqin Xian, Zeynep Akata, Gaurav Sharma, Quynh Nguyen, Matthias Hein, and Bernt Schiele · 2016
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Wasserstein generative adversarial networks
Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Improved training of wasserstein gans
Ishaan Gulrajani, Faruk Ahmed, Martin Arjovsky, Vincent Dumoulin, and Aaron C Courville · 2017
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Optimization as a model for few-shot learning
Sachin Ravi and Hugo Larochelle · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
Cited alongside, same era.
Feature generating networks for zero-shot learning
Yongqin Xian, Tobias Lorenz, Bernt Schiele, and Zeynep Akata · 2018
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Stacked semantics-guided attention model for fine-grained zero-shot learning
Yunlong Yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, and Zhongfei Zhang · 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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Adaptive confidence smoothing for generalized zero-shot learning
Yuval Atzmon and Gal Chechik · 2019
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Shifting more attention to video salient object detection
Deng-Ping Fan, Wenguan Wang, Ming-Ming Cheng, and Jianbing Shen · 2019
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Multi-modal ensemble classification for generalized zero shot learning
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Learning a deep embedding model for zero-shot learning
Li Zhang, Tao Xiang, and Shaogang Gong · 2017
Cited alongside, same era.
Multi-modal cycle-consistent generalized zero-shot learning
Rafael Felix, Vijay BG Kumar, Ian Reid, and Gustavo Carneiro · 2018
Cited alongside, same era.
Generalized zero-shot learning via synthesized examples
Vinay Kumar Verma, Gundeep Arora, Ashish Mishra, and Piyush Rai · 2018
Cited alongside, same era.
Transductive unbiased embedding for zero-shot learning
Jie Song, Chengchao Shen, Yezhou Yang, Yang Liu, and Mingli Song · 2018
Cited alongside, same era.
Learning to compare: Relation network for few-shot learning
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H S Torr, and Timothy M Hospedales · 2018
Cited alongside, same era.
Zero-shot learning via class-conditioned deep generative models
Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, and Lawrence Carin · 2018
Cited alongside, same era.
Rafael Felix, Michele Sasdelli, Ian Reid, and Gustavo Carneiro · 2019
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Generative dual adversarial network for generalized zero-shot learning
He Huang, Changhu Wang, Philip S Yu, and Chang-Dong Wang · 2019
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Leveraging the invariant side of generative zero-shot learning
Jingjing Li, Mengmeng Jin, Ke Lu, Zhengming Ding, Lei Zhu, and Zi Huang · 2019
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Gradient matching generative networks for zero-shot learning
Mert Bulent Sariyildiz and Ramazan Gokberk Cinbis · 2019
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Generalized zero-and few-shot learning via aligned variational autoencoders
Edgar Schonfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, and Zeynep Akata · 2019
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f-vaegan-d2: A feature generating framework for any-shot learning
Yongqin Xian, Saurabh Sharma, Bernt Schiele, and Zeynep Akata · 2019
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Attentive region embedding network for zero-shot learning
Guo-Sen Xie, Li Liu, Xiaobo Jin, Fan Zhu, Zheng Zhang, Jie Qin, Yazhou Yao, and Ling Shao · 2019
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Learning feature-to-feature translator by alternating back-propagation for zero-shot learning
Yizhe Zhu, Jianwen Xie, Bingchen Liu, and Ahmed Elgammal · 2019
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