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[1] Philip S. Yu,et al. Generative Dual Adversarial Network for Generalized Zero-Shot Learning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[2] Yun Fu,et al. Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[3] Shu Kong,et al. Low-Rank Bilinear Pooling for Fine-Grained Classification , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[4] Dat T. Huynh,et al. Interactive Multi-Label CNN Learning With Partial Labels , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Yoshua Bengio,et al. Mode Regularized Generative Adversarial Networks , 2016, ICLR.
[6] Marc'Aurelio Ranzato,et al. Task-Driven Modular Networks for Zero-Shot Compositional Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[7] Qixiang Ye,et al. Selective Sparse Sampling for Fine-Grained Image Recognition , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[8] Matthew A. Brown,et al. Low-Shot Learning with Imprinted Weights , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[9] Yu Qiao,et al. A Discriminative Feature Learning Approach for Deep Face Recognition , 2016, ECCV.
[10] Dacheng Tao,et al. Learning Unseen Concepts via Hierarchical Decomposition and Composition , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Trevor Darrell,et al. Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Bolei Zhou,et al. Seeing What a GAN Cannot Generate , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[13] Christoph H. Lampert,et al. Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Subhransu Maji,et al. Bilinear CNN Models for Fine-Grained Visual Recognition , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[15] XiangTao,et al. Transductive Multi-View Zero-Shot Learning , 2015 .
[16] Errui Ding,et al. Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition , 2018, ECCV.
[17] Ramesh Raskar,et al. Pairwise Confusion for Fine-Grained Visual Classification , 2017, ECCV.
[18] Zhongfei Zhang,et al. Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning , 2018, NeurIPS.
[19] H. T. Kung,et al. Stable and Efficient Representation Learning with Nonnegativity Constraints , 2014, ICML.
[20] Tao Mei,et al. Learning Multi-attention Convolutional Neural Network for Fine-Grained Image Recognition , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[21] Zhengming Ding,et al. Marginalized Latent Semantic Encoder for Zero-Shot Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Xiaogang Wang,et al. DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] Razvan Pascanu,et al. Meta-Learning with Latent Embedding Optimization , 2018, ICLR.
[24] Oriol Vinyals,et al. Neural Discrete Representation Learning , 2017, NIPS.
[25] Mohammad Norouzi,et al. Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse , 2019, NeurIPS.
[26] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[27] Dat T. Huynh,et al. Fine-Grained Generalized Zero-Shot Learning via Dense Attribute-Based Attention , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Dat T. Huynh,et al. A Shared Multi-Attention Framework for Multi-Label Zero-Shot Learning , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[29] Bernt Schiele,et al. Zero-Shot Learning — The Good, the Bad and the Ugly , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Yu-Chiang Frank Wang,et al. Multi-label Zero-Shot Learning with Structured Knowledge Graphs , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Song-Chun Zhu,et al. Attentive Fashion Grammar Network for Fashion Landmark Detection and Clothing Category Classification , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[32] Yoshua Bengio,et al. MetaGAN: An Adversarial Approach to Few-Shot Learning , 2018, NeurIPS.
[33] Oriol Vinyals,et al. Matching Networks for One Shot Learning , 2016, NIPS.
[34] Julien Rabin,et al. Detecting Overfitting of Deep Generative Networks via Latent Recovery , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[35] Xiaobo Jin,et al. Attentive Region Embedding Network for Zero-Shot Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[36] James Hays,et al. SUN attribute database: Discovering, annotating, and recognizing scene attributes , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[37] Michel Crucianu,et al. Modeling Inter and Intra-Class Relations in the Triplet Loss for Zero-Shot Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[38] Bharath Hariharan,et al. Few-Shot Learning With Localization in Realistic Settings , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Dat Huynh,et al. Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition , 2020, NeurIPS.
[40] Ying Wu,et al. Recognizing Part Attributes With Insufficient Data , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[41] Bernt Schiele,et al. Feature Generating Networks for Zero-Shot Learning , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[42] Jianwen Xie,et al. Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[43] Yang Gao,et al. Compact Bilinear Pooling , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Joshua B. Tenenbaum,et al. Meta-Learning for Semi-Supervised Few-Shot Classification , 2018, ICLR.
[45] Cewu Lu,et al. Deep LAC: Deep localization, alignment and classification for fine-grained recognition , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[46] Venkatesh Saligrama,et al. Generalized Zero-Shot Recognition Based on Visually Semantic Embedding , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[47] Xiaogang Wang,et al. Deep Learning Face Attributes in the Wild , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[48] Ali Razavi,et al. Preventing Posterior Collapse with delta-VAEs , 2019, ICLR.
[49] Jacob Andreas,et al. Measuring Compositionality in Representation Learning , 2019, ICLR.
[50] Wei-Lun Chao,et al. An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild , 2016, ECCV.
[51] Bernt Schiele,et al. Attribute Prototype Network for Zero-Shot Learning , 2020, NeurIPS.
[52] Shuqiang Jiang,et al. Multi-attention Meta Learning for Few-shot Fine-grained Image Recognition , 2020, IJCAI.
[53] Gal Chechik,et al. A causal view of compositional zero-shot recognition , 2020, NeurIPS.
[54] Abhinav Gupta,et al. Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[55] Martial Hebert,et al. Learning Compositional Representations for Few-Shot Recognition , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[56] Andrew Zisserman,et al. Deep Face Recognition , 2015, BMVC.
[57] Zhiqiang Tang,et al. Learning where to look: Semantic-Guided Multi-Attention Localization for Zero-Shot Learning , 2019, ArXiv.
[58] Bharath Hariharan,et al. Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[59] Samy Bengio,et al. Zero-Shot Learning by Convex Combination of Semantic Embeddings , 2013, ICLR.
[60] Christoph H. Lampert,et al. Attribute-Based Classification for Zero-Shot Visual Object Categorization , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[61] Fei-Fei Li,et al. Attribute Learning in Large-Scale Datasets , 2010, ECCV Workshops.
[62] Hugo Larochelle,et al. Optimization as a Model for Few-Shot Learning , 2016, ICLR.
[63] R. Devon Hjelm,et al. Locality and compositionality in zero-shot learning , 2019, ICLR.
[64] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[65] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[66] Xinge You,et al. Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition , 2018, ECCV.
[67] Martial Hebert,et al. Low-Shot Learning from Imaginary Data , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[68] Jian Ni,et al. Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning , 2019, NeurIPS.
[69] Larry S. Davis,et al. Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition , 2016, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[70] Pedro H. O. Pinheiro,et al. Adaptive Cross-Modal Few-Shot Learning , 2019, NeurIPS.
[71] Frédéric Jurie,et al. Generating Visual Representations for Zero-Shot Classification , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).
[72] Bernt Schiele,et al. Latent Embeddings for Zero-Shot Classification , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[73] Wei Shen,et al. Few-Shot Image Recognition by Predicting Parameters from Activations , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[74] Hyeonwoo Yu,et al. Zero-shot Learning via Simultaneous Generating and Learning , 2019, NeurIPS.
[75] Wei-Lun Chao,et al. Synthesized Classifiers for Zero-Shot Learning , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[76] Rogério Schmidt Feris,et al. Delta-encoder: an effective sample synthesis method for few-shot object recognition , 2018, NeurIPS.
[77] Pietro Perona,et al. Caltech-UCSD Birds 200 , 2010 .
[78] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[79] Hao Wang,et al. Rethinking Knowledge Graph Propagation for Zero-Shot Learning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[80] Ali Farhadi,et al. Describing objects by their attributes , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[81] Charles A. Sutton,et al. VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning , 2017, NIPS.
[82] Bharath Hariharan,et al. Low-Shot Visual Recognition by Shrinking and Hallucinating Features , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[83] Jo Yew Tham,et al. Learning Attribute Representations with Localization for Flexible Fashion Search , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[84] Michael I. Jordan,et al. Generalized Zero-Shot Learning with Deep Calibration Network , 2018, NeurIPS.
[85] Dacheng Tao,et al. Learning a Mixture of Granularity-Specific Experts for Fine-Grained Categorization , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[86] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[87] Bernt Schiele,et al. F-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[88] Martial Hebert,et al. From Red Wine to Red Tomato: Composition with Context , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[89] Hongyi Zhang,et al. mixup: Beyond Empirical Risk Minimization , 2017, ICLR.
[90] Deng Cai,et al. Attribute Attention for Semantic Disambiguation in Zero-Shot Learning , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[91] Martial Hebert,et al. Image Deformation Meta-Networks for One-Shot Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[92] Joshua B. Tenenbaum,et al. Human-level concept learning through probabilistic program induction , 2015, Science.
[93] Xiu-Shen Wei,et al. Multi-Label Image Recognition With Graph Convolutional Networks , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[94] Andrew Y. Ng,et al. Zero-Shot Learning Through Cross-Modal Transfer , 2013, NIPS.
[95] Ahmed M. Elgammal,et al. Link the Head to the "Beak": Zero Shot Learning from Noisy Text Description at Part Precision , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[96] Yin Li,et al. Compositional Learning for Human Object Interaction , 2018, ECCV.
[97] Venkatesh Saligrama,et al. Zero-Shot Learning via Joint Latent Similarity Embedding , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[98] Piyush Rai,et al. Generalized Zero-Shot Learning via Synthesized Examples , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[99] Gal Chechik,et al. Adaptive Confidence Smoothing for Generalized Zero-Shot Learning , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[100] Marc'Aurelio Ranzato,et al. DeViSE: A Deep Visual-Semantic Embedding Model , 2013, NIPS.
[101] Jiebo Luo,et al. Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-Grained Image Recognition , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[102] Ramazan Gokberk Cinbis,et al. Gradient Matching Generative Networks for Zero-Shot Learning , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[103] Colin Raffel,et al. Towards GAN Benchmarks Which Require Generalization , 2020, ICLR.