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Zero-shot Learning (ZSL) aims to enable classifiers to identify unseen classes.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Caltech-ucsd birds 200
Peter Welinder, Steve Branson, Takeshi Mita, Catherine Wah, Florian Schroff, Serge Belongie, and Pietro Perona · 2010
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2011
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Sun attribute database: Discovering, annotating, and recognizing scene attributes
Genevieve Patterson and James Hays · 2012
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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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An empirical study and analysis of generalized zero-shot learning for object recognition in the wild
Wei-Lun Chao, Soravit Changpinyo, Boqing Gong, and Fei Sha · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Zero-shot hashing via transferring supervised knowledge
Yang Yang, Yadan Luo, Weilun Chen, Fumin Shen, Jie Shao, and Heng Tao Shen · 2016
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Low-rank embedded ensemble semantic dictionary for zero-shot learning
Zhengming Ding, Ming Shao, and Yun Fu · 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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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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Detecting overfitting of deep generative networks via latent recovery
Ryan Webster, Julien Rabin, Loic Simon, and Frédéric Jurie · 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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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
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Latent embedding feedback and discriminative features for zero-shot classification
Sanath Narayan, Akshita Gupta, Fahad Shahbaz Khan, Cees GM Snoek, and Ling Shao · 2020
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Meta-learning for generalized zero-shot learning
Vinay Kumar Verma, Dhanajit Brahma, and Piyush Rai · 2020
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Differentiable augmentation for data-efficient gan training
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han · 2020
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Text-enhanced attribute-based attention for generalized zero-shot fine-grained image classification
Yan-He Chen and Mei-Chen Yeh · 2021
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Parametric contrastive learning
Jiequan Cui, Zhisheng Zhong, Shu Liu, Bei Yu, and Jiaya Jia · 2021
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Contrastive embedding for generalized zero-shot learning
Zongyan Han, Zhenyong Fu, Shuo Chen, and Jian Yang · 2021
Balanced contrastive learning for long-tailed visual recognition
Jianggang Zhu, Zheng Wang, Jingjing Chen, Yi-Ping Phoebe Chen, and Yu-Gang Jiang · 2022
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Evolving semantic prototype improves generative zero-shot learning
Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, and Kun Zhang · 2023
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Image-free classifier injection for zero-shot classification
Anders Christensen, Massimiliano Mancini, A. Sophia Koepke, Ole Winther, and Zeynep Akata · 2023
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Generalized parametric contrastive learning
Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, and Jiaya Jia · 2023
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Synthetic sample selection for generalized zero-shot learning
Shreyank N Gowda · 2023
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Your diffusion model is secretly a zero-shot classifier
Alexander C Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak · 2023
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A broad study on the transferability of visual representations with contrastive learning
Ashraful Islam, Chun-Fu Richard Chen, Rameswar Panda, Leonid Karlinsky, Richard Radke, and Rogerio Feris · 2021
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Improving contrastive learning on imbalanced data via open-world sampling
Ziyu Jiang, Tianlong Chen, Ting Chen, and Zhangyang Wang · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Disentangling semantic-to-visual confusion for zero-shot learning
Zihan Ye, Fuyuan Hu, Fan Lyu, Linyan Li, and Kaizhu Huang · 2021
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Rui Gao, Fan Wan, Daniel Organisciak, Jiyao Pu, Junyan Wang, Haoran Duan, Peng Zhang, Xingsong Hou, and Yang Long · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
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Progressive semantic-visual mutual adaption for generalized zero-shot learning
Man Liu, Feng Li, Chunjie Zhang, Yunchao Wei, Huihui Bai, and Yao Zhao · 2023
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Dual-aligned feature confusion alleviation for generalized zero-shot learning
Hongzu Su, Jingjing Li, Ke Lu, Lei Zhu, and Heng Tao Shen · 2023
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Rebalanced zero-shot learning
Zihan Ye, Guanyu Yang, Xiaobo Jin, Youfa Liu, and Kaizhu Huang · 2023
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Causal visual-semantic correlation for zero-shot learning
Shuhuang Chen, Dingjie Fu, Shiming Chen, Wenjin Hou, Xinge You, et al · 2024
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Text-to-image diffusion models are zero shot classifiers
Kevin Clark and Priyank Jaini · 2024
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Visual-augmented dynamic semantic prototype for generative zero-shot learning
Wenjin Hou, Shiming Chen, Shuhuang Chen, Ziming Hong, Yan Wang, Xuetao Feng, Salman Khan, Fahad Shahbaz Khan, and Xinge You · 2024
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Dyngan: Solving mode collapse in gans with dynamic clustering
Yixin Luo and Zhouwang Yang · 2024
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Data-free generalized zero-shot learning
Bowen Tang, Jing Zhang, Long Yan, Qian Yu, Lu Sheng, and Dong Xu · 2024
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Bridging the projection gap: Overcoming projection bias through parameterized distance learning
Chong Zhang, Mingyu Jin, Qinkai Yu, Haochen Xue, Shreyank N Gowda, and Xiaobo Jin · 2024
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