14.1.4.5 Zero-Shot Learning

Chapter Contents (Back)
Small Sample Size. Zero-Shot Learning. See also One Shot Learning, Few Shot Learning.

Fu, Y.W.[Yan-Wei], Hospedales, T.M., Xiang, T.[Tao], Gong, S.G.[Shao-Gang],
Transductive Multi-View Zero-Shot Learning,
PAMI(37), No. 11, November 2015, pp. 2332-2345.
IEEE DOI 1511
graph theory See also Zero-Shot Learning on Semantic Class Prototype Graph. BibRef

Kodirov, E.[Elyor], Xiang, T.[Tao], Gong, S.G.[Shao-Gang],
Semantic Autoencoder for Zero-Shot Learning,
CVPR17(4447-4456)
IEEE DOI 1711
Computational modeling, Decoding, Image reconstruction, Semantics, Training, Visualization BibRef

Kodirov, E.[Elyor], Xiang, T.[Tao], Fu, Z.Y.[Zhen-Yong], Gong, S.G.[Shao-Gang],
Unsupervised Domain Adaptation for Zero-Shot Learning,
ICCV15(2452-2460)
IEEE DOI 1602
Adaptation models See also Dictionary Learning with Iterative Laplacian Regularisation for Unsupervised Person Re-identification. See also Learning Multimodal Latent Attributes. BibRef

Fu, Y.W.[Yan-Wei], Yang, Y.X.[Yong-Xin], Hospedales, T.M.[Tim M.], Xiang, T.[Tao], Gong, S.G.[Shao-Gang],
Transductive Multi-label Zero-shot Learning,
BMVC14(xx-yy).
HTML Version. 1410
See also Learning Multimodal Latent Attributes. BibRef

Xu, X.[Xun], Hospedales, T.M.[Timothy M.], Gong, S.G.[Shao-Gang],
Multi-Task Zero-Shot Action Recognition with Prioritised Data Augmentation,
ECCV16(II: 343-359).
Springer DOI 1611
BibRef

Fu, Y.W.[Yan-Wei], Hospedales, T.M.[Timothy M.], Xiang, T.[Tao], Fu, Z.Y.[Zhen-Yong], Gong, S.G.[Shao-Gang],
Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation,
ECCV14(II: 584-599).
Springer DOI 1408
BibRef

Hoo, W.L.[Wai Lam], Chan, C.S.[Chee Seng],
Zero-Shot Object Recognition System Based on Topic Model,
HMS(45), No. 4, August 2015, pp. 518-525.
IEEE DOI 1506
BibRef
Earlier:
pLSA-based zero-shot learning,
ICIP13(4297-4301)
IEEE DOI 1402
Accuracy. Zero-shot learning; object detection; object recognition; pLSA BibRef

Cheng, Y.[Yuhu], Qiao, X.[Xue], Wang, X.[Xuesong],
An Improved Indirect Attribute Weighted Prediction Model for Zero-Shot Image Classification,
IEICE(E99-D), No. 2, February 2016, pp. 435-442.
WWW Link. 1604
BibRef

Wang, X., Chen, C., Cheng, Y.,
Zero-shot learning by exploiting class-related and attribute-related prior knowledge,
IET-CV(10), No. 6, 2016, pp. 483-492.
DOI Link 1609
data mining BibRef

Qin, J., Wang, Y., Liu, L., Chen, J., Shao, L.,
Beyond Semantic Attributes: Discrete Latent Attributes Learning for Zero-Shot Recognition,
SPLetters(23), No. 11, November 2016, pp. 1667-1671.
IEEE DOI 1609
image recognition BibRef

Qin, J., Liu, L., Shao, L., Shen, F., Ni, B., Chen, J., Wang, Y.,
Zero-Shot Action Recognition with Error-Correcting Output Codes,
CVPR17(1042-1051)
IEEE DOI 1711
Correlation, Data structures, Optimization, Pattern recognition, Robustness, Semantics, Visualization BibRef

Li, A.[Aoxue], Lu, Z.W.[Zhi-Wu], Wang, L.W.[Li-Wei], Xiang, T.[Tao], Wen, J.R.[Ji-Rong],
Zero-Shot Scene Classification for High Spatial Resolution Remote Sensing Images,
GeoRS(55), No. 7, July 2017, pp. 4157-4167.
IEEE DOI 1706
Birds, Image recognition, Remote sensing, Satellites, Semantics, Spatial resolution, Visualization, High spatial resolution (HSR) remote sensing images, scene classification, zero-shot, learning BibRef

Wang, Q.[Qian], Chen, K.[Ke],
Zero-Shot Visual Recognition via Bidirectional Latent Embedding,
IJCV(124), No. 3, September 2017, pp. 356-383.
Springer DOI 1708
BibRef

Elhoseiny, M.[Mohamed], Elgammal, A.M.[Ahmed M.], Saleh, B.[Babak],
Write a Classifier: Predicting Visual Classifiers from Unstructured Text,
PAMI(39), No. 12, December 2017, pp. 2539-2553.
IEEE DOI 1711
BibRef
Earlier: A1, A3, A2:
Write a Classifier: Zero-Shot Learning Using Purely Textual Descriptions,
ICCV13(2584-2591)
IEEE DOI 1403
Knowledge transfer, Noise measurement, Training, Visualization. Zero shot learning Use purely textual description of categories with no training images to learn visual classifiers. BibRef

Luo, C., Li, Z., Huang, K., Feng, J., Wang, M.,
Zero-Shot Learning via Attribute Regression and Class Prototype Rectification,
IP(27), No. 2, February 2018, pp. 637-648.
IEEE DOI 1712
Linear programming, Manifolds, Prototypes, Semantics, Supervised learning, Testing, Training, Zero-shot learning, transfer knowledge BibRef

Sumbul, G., Cinbis, R.G., Aksoy, S.,
Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery,
GeoRS(56), No. 2, February 2018, pp. 770-779.
IEEE DOI 1802
Data models, Feature extraction, Object recognition, Remote sensing, Spatial resolution, Training, zero-shot learning (ZSL) BibRef

Sumbul, G., Cinbis, R.G., Aksoy, S.,
Multisource Region Attention Network for Fine-Grained Object Recognition in Remote Sensing Imagery,
GeoRS(57), No. 7, July 2019, pp. 4929-4937.
IEEE DOI 1907
Object recognition, Vegetation, Laser radar, Remote sensing, Spatial resolution, Sensors, Feature extraction, Deep learning, object recognition BibRef

Long, T.[Teng], Xu, X.[Xing], Shen, F.[Fumin], Liu, L.[Li], Xie, N.[Ning], Yang, Y.[Yang],
Zero-shot learning via discriminative representation extraction,
PRL(109), 2018, pp. 27-34.
Elsevier DOI 1806
Zero shot learning, Large margin, Aggregation, Representation learning BibRef

Qiao, L.F.[Ling-Feng], Tuo, H.[Hongya], Wang, J.[Jiexin], Wang, C.[Chao], Jing, Z.L.[Zhong-Liang],
Joint attribute chain prediction for zero-shot learning,
IET-CV(12), No. 6, September 2018, pp. 873-881.
DOI Link 1808
BibRef

Qiao, L.F.[Ling-Feng], Tuo, H.[Hongya], Fang, Z., Feng, P., Jing, Z.L.[Zhong-Liang],
Joint probability estimation of attribute chain for zero-shot learning,
ICIP16(1863-1867)
IEEE DOI 1610
Classification algorithms BibRef

Long, Y., Liu, L., Shen, F., Shao, L., Li, X.,
Zero-Shot Learning Using Synthesised Unseen Visual Data with Diffusion Regularisation,
PAMI(40), No. 10, October 2018, pp. 2498-2512.
IEEE DOI 1809
Semantics, Visualization, Training, Data models, Predictive models, Training data, Zero-shot learning, data synthesis, object recognition BibRef

Long, Y., Liu, L., Shao, L., Shen, F., Ding, G., Han, J.,
From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis,
CVPR17(6165-6174)
IEEE DOI 1711
Feature extraction, Predictive models, Semantics, Training, Visualization BibRef

Gui, R.[Rong], Xu, X.[Xin], Wang, L.[Lei], Yang, R.[Rui], Pu, F.[Fangling],
A Generalized Zero-Shot Learning Framework for PolSAR Land Cover Classification,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Meng, M., Zhan, X.,
Zero-Shot Learning via Low-Rank-Representation Based Manifold Regularization,
SPLetters(25), No. 9, September 2018, pp. 1379-1383.
IEEE DOI 1809
image recognition, image representation, Laplace equations, learning (artificial intelligence), sparse matrices, zero-shot learning (ZSL) BibRef

Meng, M., Yu, J.,
Zero-Shot Learning via Robust Latent Representation and Manifold Regularization,
IP(28), No. 4, April 2019, pp. 1824-1836.
IEEE DOI 1901
geometry, image classification, image representation, learning (artificial intelligence), vectors, ZSL methods, manifold regularization BibRef

Wang, W.[Wen], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Prototype Discriminative Learning for Image Set Classification,
SPLetters(24), No. 9, September 2017, pp. 1318-1322.
IEEE DOI 1708
BibRef
Earlier:
Prototype Discriminative Learning for Face Image Set Classification,
ACCV16(III: 344-360).
Springer DOI 1704
Databases, Optimization, Prototypes, Robustness, Signal processing algorithms, Testing, Training, Discriminative learning, image set classification, prototype, learning BibRef

Jiang, H.J.[Hua-Jie], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Learning Class Prototypes via Structure Alignment for Zero-Shot Recognition,
ECCV18(X: 121-138).
Springer DOI 1810
BibRef

Liu, H.M.[Hao-Miao], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Learning Multifunctional Binary Codes for Personalized Image Retrieval,
IJCV(128), No. 8-9, September 2020, pp. 2223-2242.
Springer DOI 2008
BibRef
Earlier:
Learning Multifunctional Binary Codes for Both Category and Attribute Oriented Retrieval Tasks,
CVPR17(6259-6268)
IEEE DOI 1711
Binary codes, Data models, Image retrieval, Semantics, Training, Visualization See also Two Birds, One Stone: Jointly Learning Binary Code for Large-Scale Face Image Retrieval and Attributes Prediction. BibRef

Han, H.[Hu], Jain, A.K.[Anil K.], Wang, F.[Fang], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach,
PAMI(40), No. 11, November 2018, pp. 2597-2609.
IEEE DOI 1810
Face, Estimation, Correlation, Databases, Support vector machines, Hair, Predictive models, Face recognition, multi-task learning BibRef

Wang, F.[Fang], Han, H.[Hu], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Deep Multi-Task Learning for Joint Prediction of Heterogeneous Face Attributes,
FG17(173-179)
IEEE DOI 1707
Correlation, Databases, Face, Feature extraction, Hair, Image color analysis, Predictive, models BibRef

Mao, Y.[Yirong], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
COSONet: Compact Second-Order Network for Video Face Recognition,
ACCV18(III:51-67).
Springer DOI 1906
BibRef

Wang, W.[Wen], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Discriminative Covariance Oriented Representation Learning for Face Recognition with Image Sets,
CVPR17(5749-5758)
IEEE DOI 1711
Covariance matrices, Face, Face recognition, Feature extraction, Manifolds, Measurement, Nickel BibRef

Wang, R.P.[Rui-Ping], Guo, H.M.[Hui-Min], Davis, L.S.[Larry S.], Dai, Q.H.[Qiong-Hai],
Covariance discriminative learning: A natural and efficient approach to image set classification,
CVPR12(2496-2503).
IEEE DOI 1208
BibRef

Zhang, Y.M.[Yang-Muzi], Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Discriminative Tensor Sparse Coding for Image Classification,
BMVC13(xx-yy).
DOI Link 1402
BibRef
And:
Learning Structured Low-Rank Representations for Image Classification,
CVPR13(676-683)
IEEE DOI 1309
dictionary learning; image classification; low-rank representation BibRef

Zhang, G.X.[Guang-Xiao], Jiang, Z.L.[Zhuo-Lin], Davis, L.S.[Larry S.],
Online Semi-Supervised Discriminative Dictionary Learning for Sparse Representation,
ACCV12(I:259-273).
Springer DOI 1304
BibRef

Zheng, J.J.[Jing-Jing], Jiang, Z.L.[Zhuo-Lin],
Tag Taxonomy Aware Dictionary Learning for Region Tagging,
CVPR13(369-376)
IEEE DOI 1309
BibRef

Jiang, H.J.[Hua-Jie], Wang, R.P.[Rui-Ping], Shan, S.G.[Shi-Guang], Yang, Y.[Yi], Chen, X.L.[Xi-Lin],
Learning Discriminative Latent Attributes for Zero-Shot Classification,
ICCV17(4233-4242)
IEEE DOI 1802
image classification, image representation, learning (artificial intelligence), object recognition, ZSL task, Visualization BibRef

Zhang, H.F.[Hao-Feng], Long, Y.[Yang], Guan, Y.[Yu], Shao, L.[Ling],
Triple Verification Network for Generalized Zero-Shot Learning,
IP(28), No. 1, January 2019, pp. 506-517.
IEEE DOI 1810
Visualization, Training, Task analysis, Semantics, Benchmark testing, Degradation, Image recognition, Generalized zero shot learning, dual regression BibRef

Zhang, H.F.[Hao-Feng], Liu, L.[Li], Long, Y.[Yang], Zhang, Z.[Zheng], Shao, L.[Ling],
Deep transductive network for generalized zero shot learning,
PR(105), 2020, pp. 107370.
Elsevier DOI 2006
Generalized zero shot learning (GZSL), Transductive ZSL, KL Divergence, Deep transductive network (DTN) BibRef

Niu, L., Cai, J., Veeraraghavan, A., Zhang, L.,
Zero-Shot Learning via Category-Specific Visual-Semantic Mapping and Label Refinement,
IP(28), No. 2, February 2019, pp. 965-979.
IEEE DOI 1811
Semantics, Visualization, Training, Task analysis, Adaptation models, Feature extraction, Terminology, Zero-shot learning (ZSL), domain adaptation BibRef

Li, X.[Xiao], Fang, M.[Min], Feng, D.[Dazheng], Li, H.[Haikun], Wu, J.Q.[Jin-Qiao],
Zero shot learning by partial transfer from source domain with L2,1 norm constraint,
JVCIR(58), 2019, pp. 701-711.
Elsevier DOI 1901
Zero shot learning, Partial transfer, Visual similarity, Semantic similarity, norm BibRef

Shao, H.[Hang], Guo, Y.C.[Yu-Chen], Ding, G.G.[Gui-Guang], Han, J.G.[Jun-Gong],
Zero-shot multi-label learning via label factorisation,
IET-CV(13), No. 2, March 2019, pp. 117-124.
DOI Link 1902
BibRef

Li, X.[Xiao], Fang, M.[Min], Feng, D.[Dazheng], Li, H.[Haikun], Wu, J.Q.[Jin-Qiao],
Prototype adjustment for zero shot classification,
SP:IC(74), 2019, pp. 242-252.
Elsevier DOI 1904
Zero shot classification, Prototype adjustment, Separation, Mapping function BibRef

Yu, Y., Ji, Z., Guo, J., Zhang, Z.,
Zero-Shot Learning via Latent Space Encoding,
Cyber(49), No. 10, October 2019, pp. 3755-3766.
IEEE DOI 1907
Visualization, Prototypes, Semantics, Encoding, Task analysis, Testing, Computational modeling, Encoder-decoder framework, zero-shot learning (ZSL) BibRef

Xian, Y.Q.[Yong-Qin], Lampert, C.H., Schiele, B.[Bernt], Akata, Z.[Zeynep],
Zero-Shot Learning: A Comprehensive Evaluation of the Good, the Bad and the Ugly,
PAMI(41), No. 9, Sep. 2019, pp. 2251-2265.
IEEE DOI 1908
BibRef
Earlier: A1, A3, A4, Only:
Zero-Shot Learning: The Good, the Bad and the Ugly,
CVPR17(3077-3086)
IEEE DOI 1711
Semantics, Visualization, Task analysis, Training, Fish, Protocols, Learning systems, Generalized zero-shot learning, weakly-supervised learning. Benchmark testing, Feature extraction, See also Animals with Attributes 2 Dataset. BibRef

Jiang, H., Wang, R., Shan, S., Chen, X.,
Adaptive Metric Learning For Zero-Shot Recognition,
SPLetters(26), No. 9, September 2019, pp. 1270-1274.
IEEE DOI 1909
learning (artificial intelligence), object recognition, zero-shot recognition, zero-shot learning, semantic information, adaptive metric learning BibRef

Dutta, T., Biswas, S.,
Generalized Zero-Shot Cross-Modal Retrieval,
IP(28), No. 12, December 2019, pp. 5953-5962.
IEEE DOI 1909
Training, Protocols, Measurement, Standards, Semantics, Correlation, Training data, Cross-modal retrieval, zero-shot learning, evaluation metric BibRef

Ding, M.[Mingyu], Wang, Z.[Zhe], Lu, Z.W.[Zhi-Wu],
Cross-domain mapping learning for transductive zero-shot learning,
CVIU(187), 2019, pp. 102784.
Elsevier DOI 1909
Zero-shot learning, Semantic autoencoder, Domain adaption, Transductive learning BibRef

Jia, Z., Zhang, Z., Wang, L., Shan, C., Tan, T.,
Deep Unbiased Embedding Transfer for Zero-Shot Learning,
IP(29), No. 1, 2020, pp. 1958-1971.
IEEE DOI 1912
Visualization, Feature extraction, Semantics, Training, Seals, Prototypes, Indexes, Zero-shot learning, image classification, generative adversarial network BibRef

del Chiaro, R.[Riccardo], Bagdanov, A.D.[Andrew D.], del Bimbo, A.[Alberto],
Webly-supervised zero-shot learning for artwork instance recognition,
PRL(128), 2019, pp. 420-426.
Elsevier DOI 1912
BibRef

Changpinyo, S.[Soravit], Chao, W.L.[Wei-Lun], Gong, B.Q.[Bo-Qing], Sha, F.[Fei],
Classifier and Exemplar Synthesis for Zero-Shot Learning,
IJCV(128), No. 1, January 2020, pp. 166-201.
Springer DOI 2002
BibRef
Earlier: A1, A2, A4, Only:
Predicting Visual Exemplars of Unseen Classes for Zero-Shot Learning,
ICCV17(3496-3505)
IEEE DOI 1802
learning (artificial intelligence), object detection, object recognition, class semantic descriptions, Visualization BibRef

Chao, W.L.[Wei-Lun], Changpinyo, S.[Soravit], Gong, B.[Boqing], Sha, F.[Fei],
An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild,
ECCV16(II: 52-68).
Springer DOI 1611
BibRef
Earlier: A2, A1, A3, A4:
Synthesized Classifiers for Zero-Shot Learning,
CVPR16(5327-5336)
IEEE DOI 1612
BibRef

Huang, S., Lin, J., Huangfu, L.,
Class-Prototype Discriminative Network for Generalized Zero-Shot Learning,
SPLetters(27), 2020, pp. 301-305.
IEEE DOI 2003
Zero-shot learning, deep learning, cross-modal metric learning, relation network BibRef

Liu, Y., Tuytelaars, T.[Tinne],
A Deep Multi-Modal Explanation Model for Zero-Shot Learning,
IP(29), 2020, pp. 4788-4803.
IEEE DOI 2003
Visualization, Semantics, Task analysis, Training, Image color analysis, Head, Extraterrestrial phenomena, LSTM BibRef

Zhu, P., Wang, H., Saligrama, V.,
Zero Shot Detection,
CirSysVideo(30), No. 4, April 2020, pp. 998-1010.
IEEE DOI 2004
Semantics, Visualization, Proposals, Training, Detectors, Object detection, Training data, Zero-shot learning, convolutional neural network BibRef

Li, J., Lan, X., Long, Y., Liu, Y., Chen, X., Shao, L., Zheng, N.,
A Joint Label Space for Generalized Zero-Shot Classification,
IP(29), 2020, pp. 5817-5831.
IEEE DOI 2005
Visualization, Semantics, Prototypes, Correlation, Training, Testing, Cats, Projection learning, generalized zero-shot learning, label space BibRef

Liu, Z.Z.[Zhi-Zhe], Zhang, X.X.[Xing-Xing], Zhu, Z.F.[Zhen-Feng], Zheng, S.[Shuai], Zhao, Y.[Yao], Cheng, J.[Jian],
Convolutional prototype learning for zero-shot recognition,
IVC(98), 2020, pp. 103924.
Elsevier DOI 2006
Zero-shot recognition, Prototype learning, Image recognition, Deep learning BibRef

Zhang, X.X.[Xing-Xing], Gui, S.P.[Shu-Peng], Zhu, Z.F.[Zhen-Feng], Zhao, Y.[Yao], Liu, J.[Ji],
Hierarchical Prototype Learning for Zero-Shot Recognition,
MultMed(22), No. 7, July 2020, pp. 1692-1703.
IEEE DOI 2007
Prototypes, Visualization, Semantics, Training, Data models, Adaptation models, Object recognition, Zero-shot learning, unseen class BibRef

Pradhan, B.[Biswajeet], Al-Najjar, H.A.H.[Husam A. H.], Sameen, M.I.[Maher Ibrahim], Tsang, I.[Ivor], Alamri, A.M.[Abdullah M.],
Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Zhang, H.F.[Hao-Feng], Liu, J.R.[Jing-Ren], Yao, Y.Z.[Ya-Zhou], Long, Y.[Yang],
Pseudo distribution on unseen classes for generalized zero shot learning,
PRL(135), 2020, pp. 451-458.
Elsevier DOI 2006
Generalized zero shot learning, Pseudo distribution, Attribute similarity BibRef

Long, Y.[Yang], Shao, L.[Ling],
Describing Unseen Classes by Exemplars: Zero-Shot Learning Using Grouped Simile Ensemble,
WACV17(907-915)
IEEE DOI 1609
Benchmark testing, Feature extraction, Image color analysis, Semantics, Shape, Training, Visualization BibRef

Li, X.[Xiao], Fang, M.[Min], Li, H.[Haikun], Wu, J.Q.[Jin-Qiao],
Zero shot learning based on class visual prototypes and semantic consistency,
PRL(135), 2020, pp. 368-374.
Elsevier DOI 2006
Zero shot learning, Semantic consistency, Class visual prototypes, Shared sparse graph BibRef

Ji, Z., Cui, B., Li, H., Jiang, Y., Xiang, T., Hospedales, T.M.[Timothy M.], Fu, Y.,
Deep Ranking for Image Zero-Shot Multi-Label Classification,
IP(29), 2020, pp. 6549-6560.
IEEE DOI 2007
Testing, Training, Predictive models, Semantics, Correlation, Visualization, Training data, Multi-label classification, transductive learning BibRef

Li, X.[Xiao], Fang, M.[Min], Li, H.[Haikun], Wu, J.Q.[Jin-Qiao],
Learning discriminative and meaningful samples for generalized zero shot classification,
SP:IC(87), 2020, pp. 115920.
Elsevier DOI 2007
Generalized zero shot classification, Generative adversarial network, Class consistency, Semantic consistency BibRef

Zhang, L.[Lei], Wang, P.[Peng], Liu, L.Q.[Ling-Qiao], Shen, C.H.[Chun-Hua], Wei, W.[Wei], Zhang, Y.N.[Yan-Ning], van den Hengel, A.[Anton],
Towards Effective Deep Embedding for Zero-Shot Learning,
CirSysVideo(30), No. 9, September 2020, pp. 2843-2852.
IEEE DOI 2009
Visualization, Semantics, Training, Testing, Labeling, Computer science, Zero-shot learning, Deep embedding, Deep neural network BibRef


Han, Z.Y.[Zong-Yan], Fu, Z.Y.[Zhen-Yong], Yang, J.[Jian],
Learning the Redundancy-Free Features for Generalized Zero-Shot Object Recognition,
CVPR20(12862-12871)
IEEE DOI 2008
Semantics, Visualization, Object recognition, Redundancy, Generators, Birds, Training BibRef

Liu, S., Chen, J., Pan, L., Ngo, C., Chua, T., Jiang, Y.,
Hyperbolic Visual Embedding Learning for Zero-Shot Recognition,
CVPR20(9270-9278)
IEEE DOI 2008
Semantics, Robustness, Geometry, Feature extraction, Visualization, Image recognition, Manifolds BibRef

Huynh, D., Elhamifar, E.,
A Shared Multi-Attention Framework for Multi-Label Zero-Shot Learning,
CVPR20(8773-8783)
IEEE DOI 2008
Training, Image recognition, Semantics, Feature extraction, Task analysis, Complexity theory, Computational modeling BibRef

Brattoli, B., Tighe, J., Zhdanov, F., Perona, P., Chalupka, K.,
Rethinking Zero-Shot Video Classification: End-to-End Training for Realistic Applications,
CVPR20(4612-4622)
IEEE DOI 2008
Training, Visualization, Semantics, Task analysis, Feature extraction, Protocols BibRef

Huynh, D., Elhamifar, E.,
Fine-Grained Generalized Zero-Shot Learning via Dense Attribute-Based Attention,
CVPR20(4482-4492)
IEEE DOI 2008
Training, Semantics, Visualization, Feature extraction, Testing, Face recognition, Image recognition BibRef

Yu, Y., Ji, Z., Han, J., Zhang, Z.,
Episode-Based Prototype Generating Network for Zero-Shot Learning,
CVPR20(14032-14041)
IEEE DOI 2008
Semantics, Visualization, Prototypes, Training, Task analysis, Predictive models, Data models BibRef

Keshari, R., Singh, R., Vatsa, M.,
Generalized Zero-Shot Learning via Over-Complete Distribution,
CVPR20(13297-13305)
IEEE DOI 2008
Training, Decoding, Protocols, Databases, Mathematical model, Semantics, Gaussian distribution BibRef

Wu, J., Zhang, T., Zha, Z., Luo, J., Zhang, Y., Wu, F.,
Self-Supervised Domain-Aware Generative Network for Generalized Zero-Shot Learning,
CVPR20(12764-12773)
IEEE DOI 2008
Visualization, Semantics, Training, Data models, Image reconstruction, Bridges, Standards BibRef

Min, S., Yao, H., Xie, H., Wang, C., Zha, Z., Zhang, Y.,
Domain-Aware Visual Bias Eliminating for Generalized Zero-Shot Learning,
CVPR20(12661-12670)
IEEE DOI 2008
Visualization, Semantics, Entropy, Image recognition, Robustness, Training, Knowledge transfer BibRef

Oreshkin, B.N., Rostamzadeh, N., Pinheiro, P.O., Pal, C.,
CLAREL: Classification via retrieval loss for zero-shot learning,
VL3W20(3989-3993)
IEEE DOI 2008
Measurement, Training, Task analysis, Artificial intelligence, Probabilistic logic, Prototypes, Visualization BibRef

Samplawski, C., Learned-Miller, E., Kwon, H., Marlin, B.M.,
Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels,
VL3W20(4015-4019)
IEEE DOI 2008
Training, Benchmark testing, Maximum likelihood estimation, Semantics, Probabilistic logic, Dogs, Predictive models BibRef

Liu, Y., Li, J., Gao, X.,
A Simple Discriminative Dual Semantic Auto-encoder for Zero-shot Classification,
VL3W20(4053-4057)
IEEE DOI 2008
Semantics, Visualization, Sun, Task analysis, Feature extraction, Linear programming, Training BibRef

Li, Y., Shao, Y., Wang, D.,
Context-Guided Super-Class Inference for Zero-Shot Detection,
VL3W20(4064-4068)
IEEE DOI 2008
Feature extraction, Semantics, Convolution, Visualization, Training, Testing, Object detection BibRef

Lu, Z.Q.[Zi-Qian], Yu, Y.L.[Yun-Long], Lu, Z.M.[Zhe-Ming], Shen, F.L.[Feng-Li], Zhang, Z.F.[Zhong-Fei],
Attentive Semantic Preservation Network for Zero-Shot Learning,
EDLCV20(2919-2925)
IEEE DOI 2008
Semantics, Visualization, Task analysis, Prototypes, Training, Benchmark testing BibRef

Pambala, A.K., Dutta, T., Biswas, S.,
Generative Model with Semantic Embedding and Integrated Classifier for Generalized Zero-Shot Learning,
WACV20(1226-1235)
IEEE DOI 2006
Semantics, Visualization, Training, Generators, Task analysis, Loss measurement BibRef

Shen, J., Wang, H., Zhang, A., Qiu, Q., Zhen, X., Cao, X.,
Model-Agnostic Metric for Zero-Shot Learning,
WACV20(775-784)
IEEE DOI 2006
BibRef

Chen, Z.[Zhi], Li, J.J.[Jing-Jing], Luo, Y.D.[Ya-Dan], Huang, Z.[Zi], Yangyang, Y.Y.[Yang-Yang],
CANZSL: Cycle-Consistent Adversarial Networks for Zero-Shot Learning from Natural Language,
WACV20(863-872)
IEEE DOI 2006
Visualization, Semantics, Generators, Feature extraction, Training, Natural languages BibRef

Zhu, Y.Z.[Yi-Zhe], Xie, J.W.[Jian-Wen], Liu, B.C.[Bing-Chen], Elgammal, A.[Ahmed],
Learning Feature-to-Feature Translator by Alternating Back-Propagation for Generative Zero-Shot Learning,
ICCV19(9843-9853)
IEEE DOI 2004
backpropagation, data visualisation, feature extraction, Gaussian noise, Data models BibRef

Liu, Y., Guo, J., Cai, D., He, X.,
Attribute Attention for Semantic Disambiguation in Zero-Shot Learning,
ICCV19(6697-6706)
IEEE DOI 2004
learning (artificial intelligence), object recognition, semantic disambiguation, semantic activation, zero-shot learning, Aggregates BibRef

Li, A., Luo, T., Xiang, T., Huang, W., Wang, L.,
Few-Shot Learning With Global Class Representations,
ICCV19(9714-9723)
IEEE DOI 2004
image classification, learning (artificial intelligence), global representation, registered global class representation, Task analysis BibRef

Wu, Z., Li, Y., Guo, L., Jia, K.,
PARN: Position-Aware Relation Networks for Few-Shot Learning,
ICCV19(6658-6666)
IEEE DOI 2004
convolutional neural nets, correlation methods, feature extraction, image classification, Convolution BibRef

Gidaris, S., Bursuc, A., Komodakis, N., Pérez, P.P., Cord, M.,
Boosting Few-Shot Visual Learning With Self-Supervision,
ICCV19(8058-8067)
IEEE DOI 2004
Code, Learning.
WWW Link. feature extraction, image representation, learning (artificial intelligence), neural nets, Feature extraction BibRef

Hao, F., He, F., Cheng, J., Wang, L., Cao, J., Tao, D.,
Collect and Select: Semantic Alignment Metric Learning for Few-Shot Learning,
ICCV19(8459-8468)
IEEE DOI 2004
Code, Metric Learning.
WWW Link. image retrieval, learning (artificial intelligence), multilayer perceptrons, tensors, 3D tensor, Task analysis BibRef

Dvornik, N., Mairal, J., Schmid, C.,
Diversity With Cooperation: Ensemble Methods for Few-Shot Classification,
ICCV19(3722-3730)
IEEE DOI 2004
image classification, learning (artificial intelligence), neural nets, predictive model learning, Convolutional neural networks BibRef

Zhang, J., Zhao, C., Ni, B., Xu, M., Yang, X.,
Variational Few-Shot Learning,
ICCV19(1685-1694)
IEEE DOI 2004
Bayes methods, learning (artificial intelligence), pattern classification, statistical distributions, Prototypes BibRef

Xie, S., Li, Y., Lin, D., Nwe, T.L., Dong, S.,
Meta Module Generation for Fast Few-Shot Incremental Learning,
MDALC19(1381-1390)
IEEE DOI 2004
image classification, learning (artificial intelligence), neural nets, deep neural networks, DNNs, image classification BibRef

Peng, Z., Li, Z., Zhang, J., Li, Y., Qi, G., Tang, J.,
Few-Shot Image Recognition With Knowledge Transfer,
ICCV19(441-449)
IEEE DOI 2004
convolutional neural nets, image classification, image fusion, image recognition, inference mechanisms, Testing BibRef

Ravichandran, A., Bhotika, R., Soatto, S.,
Few-Shot Learning With Embedded Class Models and Shot-Free Meta Training,
ICCV19(331-339)
IEEE DOI 2004
image representation, learning (artificial intelligence), higher-dimensional space, embedded class models, Web services BibRef

Cacheux, Y.L., Borgne, H.L., Crucianu, M.,
Modeling Inter and Intra-Class Relations in the Triplet Loss for Zero-Shot Learning,
ICCV19(10332-10341)
IEEE DOI 2004
image representation, learning (artificial intelligence), vectors, class prototypes, implicit assumptions, Covariance matrices BibRef

Bustreo, M., Cavazza, J., Murino, V.,
Enhancing Visual Embeddings through Weakly Supervised Captioning for Zero-Shot Learning,
MDALC19(1298-1307)
IEEE DOI 2004
feature extraction, image annotation, image classification, image enhancement, learning (artificial intelligence), semantic embedding BibRef

Jin, X., Xie, G., Huang, K., Miao, J., Wang, Q.,
Beyond Attributes: High-Order Attribute Features for Zero-Shot Learning,
CEFRL19(2953-2962)
IEEE DOI 2004
feature extraction, learning (artificial intelligence), object recognition, discriminative high-order semantic vector, Feature Learning BibRef

Li, K., Min, M.R., Fu, Y.,
Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective,
ICCV19(3582-3591)
IEEE DOI 2004
entropy, feature extraction, image classification, learning (artificial intelligence), neural nets, Computer vision BibRef

Purushwalkam, S., Nickel, M., Gupta, A., Ranzato, M.,
Task-Driven Modular Networks for Zero-Shot Compositional Learning,
ICCV19(3592-3601)
IEEE DOI 2004
image classification, learning (artificial intelligence), neural nets, zero-shot classification, Semantics BibRef

Qiao, L., Shi, Y., Li, J., Tian, Y., Huang, T., Wang, Y.,
Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning,
ICCV19(3602-3611)
IEEE DOI 2004
learning (artificial intelligence), mathematical programming, pattern classification, few-shot learning, Prototypes BibRef

Elhoseiny, M., Elfeki, M.,
Creativity Inspired Zero-Shot Learning,
ICCV19(5783-5792)
IEEE DOI 2004
Code, Learning.
WWW Link. computer vision, image denoising, image recognition, learning (artificial intelligence), psychology, text analysis, ZSL, Encyclopedias BibRef

Jiang, H., Wang, R., Shan, S., Chen, X.,
Transferable Contrastive Network for Generalized Zero-Shot Learning,
ICCV19(9764-9773)
IEEE DOI 2004
learning (artificial intelligence), neural nets, object recognition, GZSL, target categories, source classes, Fuses BibRef

Wu, X.[Xixun], Song, B.[Binheng], Wang, Z.[Zhixiang], Yuan, C.[Chun],
An Inverse Mapping with Manifold Alignment for Zero-shot Learning,
MMMod20(II:400-411).
Springer DOI 2003
BibRef

Shao, Y., Li, Y., Wang, D.,
Zero-Shot Detection with Transferable Object Proposal Mechanism,
ICIP19(3666-3670)
IEEE DOI 1910
zero-shot recognition, object detection, object proposal, confidence distribution, semantic knowledge BibRef

Xie, Y., Xu, P., Ma, Z.,
Deep Zero-Shot Learning for Scene Sketch,
ICIP19(3661-3665)
IEEE DOI 1910
Scene Sketch, Zero-Shot Learning, Deep Embedding Model. BibRef

Song, J.Q.[Jian-Qiang], Shi, G.M.[Guang-Ming], Xie, X.M.[Xue-Mei], Gao, D.[Dahua],
Zero-Shot Learning Using Stacked Autoencoder with Manifold Regularizations,
ICIP19(3651-3655)
IEEE DOI 1910
Zero-shot learning, stacked autoencoder, manifold regularizers, general framework BibRef

Demirel, B., Cinbis, R.G., Ikizler-Cinbis, N.,
Learning Visually Consistent Label Embeddings for Zero-Shot Learning,
ICIP19(3656-3660)
IEEE DOI 1910
zero-shot learning, word embeddings, deep learning BibRef

Bhattacharjee, S., Mandal, D., Biswas, S.,
Autoencoder based novelty detection for generalized zero shot learning,
ICIP19(3646-3650)
IEEE DOI 1910
Generalized Zero Shot Learning, Novelty Detection, Autoencoder BibRef

Li, Y., Hu, H., Wang, D.,
Learning Visually Aligned Semantic Graph for Cross-Modal Manifold Matching,
ICIP19(3412-3416)
IEEE DOI 1910
Cross-modal learning, manifold alignment, zero-shot learning, graph matching BibRef

Guan, J.[Jiechao], Zhao, A.[An], Lu, Z.W.[Zhi-Wu],
Extreme Reverse Projection Learning for Zero-Shot Recognition,
ACCV18(I:125-141).
Springer DOI 1906
BibRef

Gao, R.[Rui], Hou, X.S.[Xing-Song], Qin, J.[Jie], Liu, L.[Li], Zhu, F.[Fan], Zhang, Z.[Zhao],
A Joint Generative Model for Zero-Shot Learning,
CEFR-LCV18(IV:631-646).
Springer DOI 1905
BibRef

Zhang, H.G.[Hong-Guang], Koniusz, P.[Piotr],
Model Selection for Generalized Zero-Shot Learning,
TASKCV18(II:198-204).
Springer DOI 1905
BibRef

Le Cacheux, Y.[Yannick], Le Borgne, H.[Hervé], Crucianu, M.[Michel],
From Classical to Generalized Zero-Shot Learning: A Simple Adaptation Process,
MMMod19(II:465-477).
Springer DOI 1901
BibRef

Li, B.L.[Bing-Lin], Wang, Y.[Yang],
Visual Relationship Detection Using Joint Visual-Semantic Embedding,
ICPR18(3291-3296)
IEEE DOI 1812
Visualization, Semantics, Feature extraction, Object detection, Task analysis, Detectors, Logic gates BibRef

Pathak, D., Mahmoudieh, P., Luo, G., Agrawal, P., Chen, D., Shentu, F., Shelhamer, E., Malik, J.[Jitendra], Efros, A.A.[Alexei A.], Darrell, T.J.[Trevor J.],
Zero-Shot Visual Imitation,
DeepLearnRV18(2131-21313)
IEEE DOI 1812
Task analysis, Robots, Visualization, Training, Navigation, Trajectory, Shape BibRef

Zhu, Y., Elhoseiny, M., Liu, B., Peng, X., Elgammal, A.,
A Generative Adversarial Approach for Zero-Shot Learning from Noisy Texts,
CVPR18(1004-1013)
IEEE DOI 1812
Visualization, Semantics, Feature extraction, Generators, Noise measurement, Encyclopedias BibRef

Song, J., Shen, C., Yang, Y., Liu, Y., Song, M.,
Transductive Unbiased Embedding for Zero-Shot Learning,
CVPR18(1024-1033)
IEEE DOI 1812
Visualization, Semantics, Training, Target recognition, Image recognition, Data models, Supervised learning BibRef

Chen, L., Zhang, H., Xiao, J., Liu, W., Chang, S.,
Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks,
CVPR18(1043-1052)
IEEE DOI 1812
Semantics, Image reconstruction, Visualization, Training, Image color analysis, Generative adversarial networks, Birds BibRef

Lee, C., Fang, W., Yeh, C., Wang, Y.F.,
Multi-label Zero-Shot Learning with Structured Knowledge Graphs,
CVPR18(1576-1585)
IEEE DOI 1812
Semantics, Task analysis, Recurrent neural networks, Correlation, Logic gates, Knowledge engineering BibRef

Verma, V.K., Arora, G., Mishra, A., Rai, P.,
Generalized Zero-Shot Learning via Synthesized Examples,
CVPR18(4281-4289)
IEEE DOI 1812
Generators, Training, Predictive models, Computer architecture, Probabilistic logic, Decoding, Image reconstruction BibRef

Xian, Y., Lorenz, T., Schiele, B., Akata, Z.,
Feature Generating Networks for Zero-Shot Learning,
CVPR18(5542-5551)
IEEE DOI 1812
Generative adversarial networks, Training, Generators, Task analysis, Training data, Feature extraction BibRef

Wang, X., Ye, Y., Gupta, A.,
Zero-Shot Recognition via Semantic Embeddings and Knowledge Graphs,
CVPR18(6857-6866)
IEEE DOI 1812
Visualization, Semantics, Training, Animals, Task analysis, Symmetric matrices, Pattern recognition BibRef

Li, Y., Zhang, J., Zhang, J., Huang, K.,
Discriminative Learning of Latent Features for Zero-Shot Recognition,
CVPR18(7463-7471)
IEEE DOI 1812
Semantics, Task analysis, Visualization, Image recognition, Training, Feature extraction, Predictive models BibRef

Biswas, S., Annadani, Y.,
Preserving Semantic Relations for Zero-Shot Learning,
CVPR18(7603-7612)
IEEE DOI 1812
Semantics, Visualization, Manganese, Linear programming, Cats, Task analysis, Manifolds BibRef

Roy, A., Banerjee, B., Murino, V.,
Discriminative Latent Visual Space For Zero-Shot Object Classification,
ICPR18(2552-2557)
IEEE DOI 1812
Visualization, Semantics, Loss measurement, Prototypes, Standards, Decoding, Task analysis BibRef

Zhang, H., Koniusz, P.,
Zero-Shot Kernel Learning,
CVPR18(7670-7679)
IEEE DOI 1812
Kernel, Task analysis, Training, Semantics, Testing, Probabilistic logic, Linear discriminant analysis BibRef

Song, J.[Jie], Shen, C.C.[Cheng-Chao], Lei, J.[Jie], Zeng, A.X.[An-Xiang], Ou, K.[Kairi], Tao, D.C.[Da-Cheng], Song, M.L.[Ming-Li],
Selective Zero-Shot Classification with Augmented Attributes,
ECCV18(IX: 474-490).
Springer DOI 1810
BibRef

Felix, R.[Rafael], Kumar, B.G.V.[B. G. Vijay], Reid, I.D.[Ian D.], Carneiro, G.[Gustavo],
Multi-modal Cycle-Consistent Generalized Zero-Shot Learning,
ECCV18(VI: 21-37).
Springer DOI 1810
BibRef

Bansal, A.[Ankan], Sikka, K.[Karan], Sharma, G.[Gaurav], Chellappa, R.[Rama], Divakaran, A.[Ajay],
Zero-Shot Object Detection,
ECCV18(I: 397-414).
Springer DOI 1810
BibRef

Wang, J., Li, Y., Pang, Z., Wang, D.,
Generating Manifold-Aligned Semantic Feature for Zero-Shot Learning,
ICIP18(1613-1617)
IEEE DOI 1809
Semantics, Visualization, Manifolds, Training, Probability distribution, Generators, Zero-shot learning, manifold alignment BibRef

Cao, X.H., Obradovic, Z., Kim, K.,
A Simple yet Effective Model for Zero-Shot Learning,
WACV18(766-774)
IEEE DOI 1806
computer vision, image classification, image representation, learning (artificial intelligence), baseline models, Training BibRef

Liu, Q.L.[Qiu-Li], Li, Z.C.[Ze-Chao], Tang, J.H.[Jin-Hui],
Learning discriminative supplementary features to attributes for novel-category classification,
VCIP17(1-4)
IEEE DOI 1804
category theory, image classification, image representation, learning (artificial intelligence), Supplementary Feature BibRef

Xue, N., Wang, Y., Fan, X., Min, M.,
Incremental zero-shot learning based on attributes for image classification,
ICIP17(850-854)
IEEE DOI 1803
Linear matrix inequalities, Matrix decomposition, Object recognition, Pattern recognition, Software, zero-shot BibRef

Jia, Z., Zhang, J., Huang, K., Tan, T.,
Encyclopedia enhanced semantic embedding for zero-shot learning,
ICIP17(1287-1291)
IEEE DOI 1803
Encyclopedias, Mathematical model, Prototypes, Semantics, Task analysis, Training, image classification, zero-shot learning BibRef

Zhao, B., Wu, B., Wu, T., Wang, Y.,
Zero-Shot Learning Posed as a Missing Data Problem,
TASKCV17(2616-2622)
IEEE DOI 1802
Animals, Feature extraction, Gaussian distribution, Manifolds, Training, Training data, Upper bound BibRef

Demirel, B., Cinbis, R.G., Ikizler-Cinbis, N.,
Attributes2Classname: A Discriminative Model for Attribute-Based Unsupervised Zero-Shot Learning,
ICCV17(1241-1250)
IEEE DOI 1802
feature extraction, image annotation, learning (artificial intelligence), text analysis, vectors, Visualization BibRef

Xu, X.[Xing], Shen, F.[Fumin], Yang, Y.[Yang], Zhang, D.X.[Dong-Xiang], Shen, H.T.[Heng Tao], Song, J.K.[Jing-Kuan],
Matrix Tri-Factorization with Manifold Regularizations for Zero-Shot Learning,
CVPR17(2007-2016)
IEEE DOI 1711
Feature extraction, Manifolds, Matrix decomposition, Semantics, Training, Training data, Visualization BibRef

Morgado, P., Vasconcelos, N.M.,
Semantically Consistent Regularization for Zero-Shot Recognition,
CVPR17(2037-2046)
IEEE DOI 1711
Computational modeling, Image recognition, Pattern recognition, Semantics, Training, Visualization, Vocabulary BibRef

Li, Y., Wang, D., Hu, H., Lin, Y., Zhuang, Y.,
Zero-Shot Recognition Using Dual Visual-Semantic Mapping Paths,
CVPR17(5207-5215)
IEEE DOI 1711
Feature extraction, Machine learning, Manifolds, Optimization, Semantics, Testing BibRef

Deutsch, S., Kolouri, S., Kim, K., Owechko, Y., Soatto, S.,
Zero Shot Learning via Multi-scale Manifold Regularization,
CVPR17(5292-5299)
IEEE DOI 1711
Benchmark testing, Manifolds, Semantics, Training, Unsupervised learning, Visualization, Wavelet, domain BibRef

Markowitz, J., Schmidt, A.C., Burlina, P.M., Wang, I.J.,
Hierarchical zero-shot classification with convolutional neural network features and semantic attribute learning,
MVA17(194-197)
DOI Link 1708
Buildings, Neural networks, Organizations, Semantics, Support vector machines, Training, Training, data BibRef

Naha, S., Wang, Y.,
Object figure-ground segmentation using zero-shot learning,
ICPR16(2842-2847)
IEEE DOI 1705
Image segmentation, Knowledge transfer, Object segmentation, Semantics, Standards, Training, Visualization BibRef

Dolma, Y.[Yeshi], Namboodiri, V.P.[Vinay P.],
Using Gaussian Processes to Improve Zero-Shot Learning with Relative Attributes,
ACCV16(V: 150-164).
Springer DOI 1704
BibRef

Li, H.H.[Han-Hui], Wu, H.F.[He-Feng], Lin, S.J.[Shu-Jin], Lin, L.[Liang], Luo, X.N.[Xiao-Nan], Izquierdo, E.[Ebroul],
Boosting Zero-Shot Image Classification via Pairwise Relationship Learning,
ACCV16(I: 85-99).
Springer DOI 1704
BibRef

Xian, Y., Akata, Z.[Zeynep], Sharma, G., Nguyen, Q., Hein, M.[Matthias], Schiele, B.[Bernt],
Latent Embeddings for Zero-Shot Classification,
CVPR16(69-77)
IEEE DOI 1612
BibRef

Qiao, R., Liu, L., Shen, C., van den Hengel, A.J.[Anton J.],
Less is More: Zero-Shot Learning from Online Textual Documents with Noise Suppression,
CVPR16(2249-2257)
IEEE DOI 1612
BibRef

Al-Halah, Z., Stiefelhagen, R.,
Automatic Discovery, Association Estimation and Learning of Semantic Attributes for a Thousand Categories,
CVPR17(5112-5121)
IEEE DOI 1711
Data models, Estimation, Predictive models, Semantics, Visualization, Vocabulary BibRef

Al-Halah, Z., Tapaswi, M., Stiefelhagen, R.,
Recovering the Missing Link: Predicting Class-Attribute Associations for Unsupervised Zero-Shot Learning,
CVPR16(5975-5984)
IEEE DOI 1612
BibRef

Zhang, Y., Gong, B., Shah, M.,
Fast Zero-Shot Image Tagging,
CVPR16(5985-5994)
IEEE DOI 1612
BibRef

Akata, Z.[Zeynep], Malinowski, M., Fritz, M.[Mario], Schiele, B.[Bernt],
Multi-cue Zero-Shot Learning with Strong Supervision,
CVPR16(59-68)
IEEE DOI 1612
BibRef

Jurie, F.[Frédéric], Bucher, M.[Maxime], Herbin, S.[Stéphane],
Generating Visual Representations for Zero-Shot Classification,
TASKCV17(2666-2673)
IEEE DOI 1802
BibRef
Earlier: A2, A3, A1:
Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classiffication,
ECCV16(V: 730-746).
Springer DOI 1611
BibRef
And: A2, A3, A1:
Hard Negative Mining for Metric Learning Based Zero-Shot Classification,
TASKCV16(III: 524-531).
Springer DOI 1611
Data models, Generators, Gold, Semantics, Training, Visualization BibRef

Ye, M., Guo, Y.,
Zero-Shot Classification with Discriminative Semantic Representation Learning,
CVPR17(5103-5111)
IEEE DOI 1711
Dictionaries, Encoding, Prototypes, Semantics, Sparse matrices, Training, Visualization BibRef

Ye, M.[Meng], Guo, Y.H.[Yu-Hong],
Multi-Label Zero-Shot Learning With Transfer-Aware Label Embedding Projection,
ICIP19(3671-3675)
IEEE DOI 1910
Zero-shot learning, multi-label classification, label embedding, auxiliary information BibRef

Li, X.[Xin], Guo, Y.H.[Yu-Hong], Schuurmans, D.[Dale],
Semi-Supervised Zero-Shot Classification with Label Representation Learning,
ICCV15(4211-4219)
IEEE DOI 1602
Adaptation models BibRef

Zhang, Z.M.[Zi-Ming], Saligrama, V.[Venkatesh],
Zero-Shot Learning via Joint Latent Similarity Embedding,
CVPR16(6034-6042)
IEEE DOI 1612
BibRef
And:
Zero-Shot Recognition via Structured Prediction,
ECCV16(VII: 533-548).
Springer DOI 1611
BibRef
Earlier:
Zero-Shot Learning via Semantic Similarity Embedding,
ICCV15(4166-4174)
IEEE DOI 1602
Benchmark testing See also PRISM: Person Reidentification via Structured Matching. BibRef

Yang, Y.X.[Yong-Xin], Hospedales, T.M.[Timothy M.],
Multivariate Regression on the Grassmannian for Predicting Novel Domains,
CVPR16(5071-5080)
IEEE DOI 1612
BibRef
Earlier:
Zero-Shot Domain Adaptation via Kernel Regression on the Grassmannian,
DIFF-CV15(xx-yy).
DOI Link 1601
BibRef

Naha, S.[Shujon], Wang, Y.[Yang],
Zero-Shot Object Recognition Using Semantic Label Vectors,
CRV15(94-100)
IEEE DOI 1507
Computer vision. Given images and training images, recognize another non-overlapping class with no training examples. BibRef

Fu, Z.Y.[Zhen-Yong], Xiang, T.A.[Tao A.], Kodirov, E.[Elyor], Gong, S.G.[Shao-Gang],
Zero-shot object recognition by semantic manifold distance,
CVPR15(2635-2644)
IEEE DOI 1510
BibRef

Al-Halah, Z.[Ziad], Stiefelhagen, R.[Rainer],
How to Transfer? Zero-Shot Object Recognition via Hierarchical Transfer of Semantic Attributes,
WACV15(837-843)
IEEE DOI 1503
Abstracts;Accuracy;Birds;Semantics;Testing;Training;Visualization BibRef

Jetley, S.[Saumya], Romera-Paredes, B.[Bernardino], Jayasumana, S.[Sadeep], Torr, P.H.S.[Philip H.S.],
Prototypical Priors: From Improving Classification to Zero-Shot Learning,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Liu, L.C.[Liang-Chen], Wiliem, A.[Arnold], Chen, S.K.[Shao-Kang], Lovell, B.C.[Brian C.],
Automatic and quantitative evaluation of attribute discovery methods,
WACV16(1-9)
IEEE DOI 1606
BibRef
Earlier:
Automatic Image Attribute Selection for Zero-Shot Learning of Object Categories,
ICPR14(2619-2624)
IEEE DOI 1412
Binary codes. Animals BibRef

Antol, S.[Stanislaw], Agrawal, A.[Aishwarya], Lu, J.[Jiasen], Mitchell, M.[Margaret], Batra, D.[Dhruv], Zitnick, C.L.[C. Lawrence], Parikh, D.[Devi],
VQA: Visual Question Answering,
ICCV15(2425-2433)
IEEE DOI 1602
Cognition See also VQA: Visual Question Answering. BibRef

Antol, S.[Stanislaw], Zitnick, C.L.[C. Lawrence], Parikh, D.[Devi],
Zero-Shot Learning via Visual Abstraction,
ECCV14(IV: 401-416).
Springer DOI 1408
Categories described by text BibRef

Kankuekul, P.[Pichai], Kawewong, A.[Aram], Tangruamsub, S.[Sirinart], Hasegawa, O.[Osamu],
Online incremental attribute-based zero-shot learning,
CVPR12(3657-3664).
IEEE DOI 1208
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
One Shot Learning, Few Shot Learning .


Last update:Sep 14, 2020 at 15:32:18