Research progress of zero-shot learning beyond computer vision

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155 · see citing works

ImageNet: A large-scale hierarchical image database

Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206848 · Cited by 65,333 · see citing works

Efficient Estimation of Word Representations in Vector Space

Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1301.3781 · Cited by 26,568 · see citing works

GAN（Generative Adversarial Nets）

淳司, 柴. (2017) · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics · doi:10.3156/jsoft.29.5_177_2 · Cited by 19,268 · see citing works

Caltech-UCSD Birds-200-2011 Dataset

Wah, C. (2024) · CaltechAUTHORS (California Institute of Technology) · doi:10.57702/i9oeewf6 · Cited by 3,875 · see citing works

Automated Flower Classification over a Large Number of Classes

Nilsback, M.-E., & Zisserman, A. (2008) · 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing · doi:10.1109/icvgip.2008.47 · Cited by 3,442 · see citing works

DeViSE: A Deep Visual-Semantic Embedding Model

Frome, A., Corrado, G. S., Shlens, J., Samy Bengio, A., Dean, J., Ranzato, M., & Mikolov, T. (2013) · Cited by 2,309 · see citing works

Describing objects by their attributes

Farhadi, A., Endres, I., Hoiem, D., & Forsyth, D. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206772 · Cited by 1,917 · see citing works

Learning to detect unseen object classes by between-class attribute transfer

Lampert, C. H., Nickisch, H., & Harmeling, S. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206594 · Cited by 1,849 · see citing works

Zero-Shot Learning—A Comprehensive Evaluation of the Good, the Bad and the Ugly

Xian, Y., Lampert, C. H., Schiele, B., & Akata, Z. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2857768 · Cited by 1,678 · see citing works

Attribute-Based Classification for Zero-Shot Visual Object Categorization

Lampert, C. H., Nickisch, H., & Stefan Harmeling, B. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.140 · Cited by 1,639 · see citing works

Learning to detect unseen object classes by between-class attribute transfer

Lampert, C. H., Nickisch, H., & Stefan Harmeling, B. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvprw.2009.5206594 · Cited by 1,563 · see citing works

An Embarrassingly Simple Approach to Zero-Shot Learning

Romera‐Paredes, B., & Torr, P. H. S. (2017) · Advances in computer vision and pattern recognition · doi:10.1007/978-3-319-50077-5_2 · Cited by 1,113 · see citing works

Feature Generating Networks for Zero-Shot Learning

Xian, Y., Lorenz, T., Schiele, B., & Akata, Z. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00581 · Cited by 1,080 · see citing works

Evaluation of output embeddings for fine-grained image classification

Akata, Z., Reed, S., Walter, D., Lee, H., & Schiele, B. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298911 · Cited by 1,011 · see citing works

Semantic Autoencoder for Zero-Shot Learning

Kodirov, E., Xiang, T., & Gong, S. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.473 · Cited by 960 · see citing works

Zero-Shot Learning — The Good, the Bad and the Ugly

Xian, Y., Schiele, B., & Akata, Z. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.328 · Cited by 891 · see citing works

Zero-Shot Learning by Convex Combination of Semantic EmbeddingsPreprint

Norouzi, M., Mikolov, T., Samy Bengio, A., Singer, Y., Shlens, J., Frome, A., Corrado, G. S., & Dean, J. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1312.5650 · Cited by 890 · see citing works

SUN attribute database: Discovering, annotating, and recognizing scene attributes

Patterson, G., & Hays, J. H. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247998 · Cited by 878 · see citing works

Label-Embedding for Image Classification

Akata, Z., Perronnin, F., Harchaoui, Z., & Schmid, C. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2487986 · Cited by 785 · see citing works

Zero-Shot Learning with Semantic Output Codes

Palatucci, M., Pomerleau, D., Hinton, G. E., & Mitchell, T. M. (2018) · Figshare · doi:10.1184/r1/6476456 · Cited by 752 · see citing works

Representation Learning of Knowledge Graphs with Entity Descriptions

Xie, R., Liu, Z., Jia, J., Luan, H., & Sun, M. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.10329 · Cited by 725 · see citing works

Latent Embeddings for Zero-Shot Classification

Xian, Y., Akata, Z., Sharma, G., Nguyen, Q., Hein, M., & Schiele, B. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.15 · Cited by 723 · see citing works

Synthesized Classifiers for Zero-Shot Learning

Changpinyo, S., Chao, W., Gong, B., & Sha, F. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.575 · Cited by 720 · see citing works

Zero-Shot Learning via Semantic Similarity Embedding

Zhang, Z., & Saligrama, V. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.474 · Cited by 629 · see citing works

An Empirical Study and Analysis of Generalized Zero-Shot Learning for Object Recognition in the Wild

Chao, W.-L., Changpinyo, S., Gong, B., & Sha, F. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46475-6_4 · Cited by 616 · see citing works

Evaluation of Output Embeddings for Fine-grained Image Classification

Akata, Z., Reed, S., Walter, D., Lee, H., & Schiele, B. (2015) · Max Planck Digital Library · Cited by 567 · see citing works

A review on neural networks with random weights

Cao, W., Wang, X., Ming, Z., & Gao, J. (2017) · Neurocomputing · doi:10.1016/j.neucom.2017.08.040 · Cited by 472 · see citing works

Multi-modal Cycle-Consistent Generalized Zero-Shot Learning

Felix, R., Kumar, B. G. V., Reid, I. D., & Carneiro, G. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-01231-1_2 · Cited by 391 · see citing works

Zero-data learning of new tasks

Larochelle, H., Erhan, D., & Bengio, Y. (2008) · Cited by 345 · see citing works

Big data analytics for preventive medicine

Razzak, I., Imran, M. A., & Xu, G. (2019) · Neural Computing and Applications · doi:10.1007/s00521-019-04095-y · Cited by 332 · see citing works

Improving zero-shot learning by mitigating the hubness problem

Dinu, G., Lazaridou, A., & Baroni, M. (2015) · Figshare · doi:10.5281/zenodo.2654863 · Cited by 320 · see citing works

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement LearningPreprint

Oh, J., Singh, S., Lee, H., & Kohli, P. (2017) · International Conference on Machine Learning · doi:10.48550/arxiv.1706.05064 · Cited by 292 · see citing works

Transductive Unbiased Embedding for Zero-Shot Learning

Song, J., Shen, C., Yang, Y., Liu, Y., & Song, M. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00113 · Cited by 241 · see citing works

Transductive Multi-view Embedding for Zero-Shot Recognition and Annotation

Fu, Y., Hospedales, T. M., Xiang, T., Fu, Z., & Gong, S. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10605-2_38 · Cited by 231 · see citing works

A Simple Exponential Family Framework for Zero-Shot Learning

Verma, V. K., & Rai, P. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-71246-8_48 · Cited by 216 · see citing works

Hubness and Pollution: Delving into Cross-Space Mapping for Zero-Shot Learning

Lazaridou, A., Dinu, G., & Baroni, M. (2015) · doi:10.3115/v1/p15-1027 · Cited by 212 · see citing works

Zero-Shot Recognition Using Dual Visual-Semantic Mapping Paths

Li, Y., Wang, D., Hu, H., Lin, Y., & Zhuang, Y. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.553 · Cited by 152 · see citing works

Cross-domain activity recognition

Zheng, V. W., Hu, D. H., & Yang, Q. (2009) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/1620545.1620554 · Cited by 133 · see citing works

Zero-Shot Classification with Discriminative Semantic Representation Learning

Ye, M., & Guo, Y. (2017) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2017.542 · Cited by 129 · see citing works

Physical-layer fingerprinting of LoRa devices using supervised and zero-shot learning

Robyns, P., Marin, E., Lamotte, W., Quax, P., Singelée, D., & Bart Preneel, A. (2017) · ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec) · doi:10.1145/3098243.3098267 · Cited by 125 · see citing works

NuActiv

Cheng, H.-T., Sun, F.-T., Griss, M., Davis, P., Li, J., & You, D. (2013) · International Conference on Mobile Systems, Applications, and Services · doi:10.1145/2462456.2464438 · Cited by 117 · see citing works

Label Embedding for Zero-shot Fine-grained Named Entity Typing.

Ma, Y., Cambria, E., & Gao, S. (2016) · International Conference on Computational Linguistics · Cited by 116 · see citing works

Alleviating Feature Confusion for Generative Zero-shot Learning

Li, J., Jing, M., Lü, K., Zhu, L., Yang, Y., & Huang, Z. H. (2019) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3343031.3350901 · Cited by 78 · see citing works

Zero-shot Entity Extraction from Web Pages

Pasupat, P., & Liang, P. (2014) · Annual Meeting of the Association for Computational Linguistics (ACL) · doi:10.3115/v1/p14-1037 · Cited by 45 · see citing works

Image-Mediated Learning for Zero-Shot Cross-Lingual Document Retrieval

Funaki, R., & Nakayama, H. (2015) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d15-1070 · Cited by 37 · see citing works

Zero-shot semantic parser for spoken language understanding

Ferreira, E., Jabaian, B., & Lefèvre, F. (2015) · Interspeech (USB) · doi:10.21437/interspeech.2015-57 · Cited by 37 · see citing works

A study on the relationship between the rank of input data and the performance of random weight neural network

Cao, W., Hu, L., Gao, J., Wang, X., & Ming, Z. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-04719-8 · Cited by 35 · see citing works

A Unified Multiplicative Framework for Attribute Learning

Liang, K., Chang, H., Shan, S., & Chen, X. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.288 · Cited by 34 · see citing works

Knowledge Distillation for Bilingual Dictionary Induction

Nakashole, N., & Flauger, R. (2017) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d17-1264 · Cited by 26 · see citing works

A decadal survey of zero-shot image classification

Pang, Y., Wang, H., Yu, Y., & Ji, Z. (2019) · Scientia Sinica Informationis · doi:10.1360/n112018-00312 · Cited by 16 · see citing works

Feature Selection Methods for Zero-Shot Learning of Neural Activity

Caceres, C. A., Roos, M. J., Rupp, K., Milsap, G., Crone, N. E., Wolmetz, M. E., & Ratto, C. R. (2017) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2017.00041 · Cited by 14 · see citing works

A Biologically Inspired Feature Enhancement Framework for Zero-Shot Learning

Xie, Z., Cao, W., Wang, X., Ming, Z., Zhang, J., & Zhang, J. (2020) · IEEE International Conference on Cyber Security and Cloud Computing / IEEE International Conference on Edge Computing and Scalable Cloud (CSCloud/EdgeCom) · doi:10.1109/cscloud-edgecom49738.2020.00028 · Cited by 7 · see citing works

A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects

Pauly, L., Rharbaoui, W., Shneider, C., Rathinam, A., Gaudillière, V., & Aouada, D. (2023) · Acta Astronautica · doi:10.1016/j.actaastro.2023.08.001 · Cited by 121 · see citing works

Exploring AI-driven approaches for unstructured document analysis and future horizons

Mahadevkar, S. V., Patil, S., Kotecha, K. V., Soong, L. W., & Choudhury, T. (2024) · Journal Of Big Data · doi:10.1186/s40537-024-00948-z · Cited by 93 · see citing works

A review on multimodal zero‐shot learning

Cao, W., Wu, Y., Sun, Y., Zhang, H., Ren, J., Gu, D., & Wang, X. (2023) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi:10.1002/widm.1488 · Cited by 50 · see citing works

Sustainable and Transferable Traffic Sign Recognition for Intelligent Transportation Systems

Cao, W., Wu, Y., Chakraborty, C., Li, D., Zhao, L., & Ghosh, S. K. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3215572 · Cited by 30 · see citing works

Generalized Zero-Shot Learning for Fault Diagnosis in High-Speed Train Bogies Based on Enhanced Diffusion Generative Models

Qin, N., Yin, Y., Huang, D., You, Y., & Hou, R. (2024) · IEEE Transactions on Reliability · doi:10.1109/tr.2024.3425437 · Cited by 18 · see citing works

A Survey of Zero-Shot Object Detection

Cao, W., Yao, X., Xu, Z., Ye, L., Pan, Y., & Ming, Z. (2025) · Big Data Mining and Analytics · doi:10.26599/bdma.2024.9020098 · Cited by 17 · see citing works

AdaDerivative optimizer: Adapting step-sizes by the derivative term in past gradient information

Zou, W., Xia, Y., & Cao, W. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.105755 · Cited by 14 · see citing works

Learning Resource Recommendation in E-Learning Systems Based on Online Learning Style

Yan, L., Yin, C., Chen, H., Rong, W., Xiong, Z., & David, B. T. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-82153-1_31 · Cited by 13 · see citing works

Meta-DZSL: a meta-dictionary learning based approach to zero-shot recognition

Singh, U. P., Singh, K. P., & Thakur, M. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03257-1 · Cited by 7 · see citing works

NucNormZSL: nuclear norm-based domain adaptation in zero-shot learning

Singh, U. P., Singh, K. P., & Thakur, M. (2021) · Neural Computing and Applications · doi:10.1007/s00521-021-06461-1 · Cited by 5 · see citing works

Task Tree Partition and Subtree Allocation for Heterogeneous Multiprocessors

He, S., Wu, J., Wei, B., & Wu, J. (2021) · IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA) · doi:10.1109/ispa-bdcloud-socialcom-sustaincom52081.2021.00084 · Cited by 5 · see citing works

Intelligent Adaptive Anisotropic Diffusion Filtered Deep Neural Network With Gaussian Activation For Image Classification

Praveenkumar, G. D., & Nagaraj, R. (2022) · International Conference on Computing Methodologies and Communication (ICCMC) · doi:10.1109/iccmc53470.2022.9753971 · Cited by 4 · see citing works

WGGAL: A Practical Time Series Forecasting Framework for Dynamic Cloud Environments

Qiu, Y., Cao, W., Xiao, Z., Ming, Z., Ji, C., Gu, J., Cao, C., & Zheng, L. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5498-4_2 · Cited by 2 · see citing works

Zero-shot learning via visual-semantic aligned autoencoder

Wei, T., Huang, J., & Jin, C. (2023) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2023629 · Cited by 1 · see citing works

A novel traffic sign recognition approach for open scenarios

Cao, W., Yuhao, W. U., Dachuan, L. I., Zhong, M. I. N. G., Chen, Z., & Ye, X. (2023) · JOURNAL OF SHENZHEN UNIVERSITY SCIENCE AND ENGINEERING · doi:10.3724/sp.j.1249.2023.03258 · Cited by 1 · see citing works

MetaVSR: A Novel Approach to Video Super-Resolution for Arbitrary Magnification

Hong, Z., Cao, W., Xu, Z., Chen, Z., Tao, X., Ming, Z., Cao, C., & Zheng, L. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53305-1_23 · Cited by 1 · see citing works

Charge Prediction for Criminal Law with Semantic Attributes

Zhou, C., Cao, W., & Xu, Z. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-97774-0_19 · Cited by 1 · see citing works

Cop: Continuously Pairing of Heterogeneous Wearable Devices Based on Heartbeat

He, W., Lin, J., Zou, Y., & Cao, W. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5498-4_20

A Novel Network Intrusion Detection Method for Unbalanced Data in Open Scenarios

Gong, Z., Wang, Q., He, W., Cao, C., Zheng, L., & Yu, Y. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-5489-2_25

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning

Cao, W., Yao, X., Xu, Z., Pan, Y., Sun, Y., Li, D., Qiu, B., & Wei, M. (2024) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin58382.2024.10774475

Enhancing Smartphone-Based Gait Authentication: A Comprehensive Review of Methods and the Potential of Zero-Shot Learning

Rajeev, J., & Nair, P. P. (2025) · International Conference on Advancements in Power, Communication and Intelligent Systems (APCI) · doi:10.1109/apci65531.2025.11137207

Research progress of zero-shot learning

Sun, X., Gu, J., & Sun, H. (2020) · Applied Intelligence · doi:10.1007/s10489-020-02075-7 · Cited by 65 · see citing works

From Classical to Generalized Zero-Shot Learning: A Simple Adaptation Process

Cacheux, Y. L., Borgne, H. L., & Crucianu, M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-05716-9_38 · Cited by 1 · see citing works

Zero-Shot Learning for Computer Vision Applications

Sarma, S. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3613435 · Cited by 2 · see citing works

A survey on Zero-shot learning

Song, F., & Chen, Y. (2016) · Cited by 2 · see citing works

A comprehensive review on zero-shot-learning techniques

Lazaros, K., Koumadorakis, D. E., Vrahatis, A. G., & Kotsiantis, S. B. (2024) · Intelligent Decision Technologies · doi:10.3233/idt-240297 · Cited by 6 · see citing works