14.1.9.5.1 Compositional Zero-Shot Learning

Chapter Contents (Back)
Zero-Shot Learning. Compositional Learning. Recognize novel compositions of primitives.
See also Open Set, Open World Recongnition.

Dong, H.Z.[Han-Ze], Fu, Y.W.[Yan-Wei], Hwang, S.J.[Sung Ju], Sigal, L.[Leonid], Xue, X.Y.[Xiang-Yang],
Learning the Compositional Domains for Generalized Zero-shot Learning,
CVIU(221), 2022, pp. 103454.
Elsevier DOI 2206
Generalized Zero-shot Learning, Open Set Learning, Domain division BibRef

Xu, Z.W.[Zi-Wei], Wang, G.Z.[Guang-Zhi], Wong, Y.K.[Yong-Kang], Kankanhalli, M.S.[Mohan S.],
Relation-Aware Compositional Zero-Shot Learning for Attribute-Object Pair Recognition,
MultMed(24), 2022, pp. 3652-3664.
IEEE DOI 2207
Visualization, Task analysis, Semantics, Training, Image recognition, Feature extraction, Computational modeling, message passing BibRef

Patil, C.[Charulata], Abhyankar, A.[Aditya],
Decoupled contributed attribute-object composition detection,
IVC(131), 2023, pp. 104630.
Elsevier DOI 2303
Compositional zero shot learning, Composite representation learning, Attribute detection, Computer vision BibRef

Yang, M.[Muli], Xu, C.H.[Cheng-Hao], Wu, A.[Aming], Deng, C.[Cheng],
A Decomposable Causal View of Compositional Zero-Shot Learning,
MultMed(25), 2023, pp. 5892-5902.
IEEE DOI 2311
BibRef

Yang, Y.H.[Yan-Hua], Pan, R.[Rui], Li, X.Y.[Xiang-Yu], Yang, X.[Xu], Deng, C.[Cheng],
Dual-Stream Contrastive Learning for Compositional Zero-Shot Recognition,
MultMed(26), 2024, pp. 1909-1919.
IEEE DOI 2402
Visualization, Task analysis, Correlation, Semantics, Training, Prototypes, Feature extraction, Compositional Zero-Shot learning, transfer learning BibRef

Li, X.Y.[Xiang-Yu], Yang, X.[Xu], Wei, K.[Kun], Deng, C.[Cheng], Yang, M.[Muli],
Siamese Contrastive Embedding Network for Compositional Zero-Shot Learning,
CVPR22(9316-9325)
IEEE DOI 2210
Training, Deep learning, Visualization, Prototypes, Training data, Robustness, Transfer/low-shot/long-tail learning, Deep learning architectures and techniques BibRef

Jiang, C.[Chenyi], Ye, Q.L.[Qiao-Lin], Wang, S.D.[Shi-Dong], Shen, Y.M.[Yu-Ming], Zhang, Z.[Zheng], Zhang, H.F.[Hao-Feng],
Mutual Balancing in State-Object Components for Compositional Zero-Shot Learning,
PR(152), 2024, pp. 110451.
Elsevier DOI Code:
WWW Link. 2405
Compositional Zero-Shot Learning, Image classification, Visual-attribute, Mutual Balancing BibRef

Shuang, F.[Feng], Li, J.H.[Jia-Huan], Huang, Q.B.[Qing-Bao], Zhao, W.[Wenye], Xu, D.S.[Dong-Sheng], Han, C.[Chao], Cheng, H.[Haonan],
Visual primitives as words: Alignment and interaction for compositional zero-shot learning,
PR(157), 2025, pp. 110814.
Elsevier DOI 2409
Compositional zero-shot learning, Attribute-object composition, Vision-language model, Prompt tuning BibRef

Liu, Y.[Yu], Li, J.H.[Jiang-Hao], Zhang, Y.[Yanyi], Jia, Q.[Qi], Wang, W.M.[Wei-Min], Pu, N.[Nan], Sebe, N.[Nicu],
PMGNet: Disentanglement and entanglement benefit mutually for compositional zero-shot learning,
CVIU(249), 2024, pp. 104197.
Elsevier DOI 2412
Compositional Zero-shot Learning, Contextuality, Generalizability, Mutual Learning BibRef

Panda, A.[Aditya], Mukherjee, D.P.[Dipti Prasad],
Compositional Zero-Shot Learning using Multi-Branch Graph Convolution and Cross-layer Knowledge Sharing,
PR(145), 2024, pp. 109916.
Elsevier DOI 2311
Compositional zero shot, Knowledge sharing, State-object composition, Feasibility assessment, Graph convolution BibRef

Liu, Z.[Zhe], Li, Y.[Yun], Yao, L.[Lina], Chang, X.J.[Xiao-Jun], Fang, W.[Wei], Wu, X.J.[Xiao-Jun], El Saddik, A.[Abdulmotaleb],
Simple Primitives With Feasibility- and Contextuality-Dependence for Open-World Compositional Zero-Shot Learning,
PAMI(46), No. 1, January 2024, pp. 543-560.
IEEE DOI 2312
BibRef

Mancini, M.[Massimiliano], Naeem, M.F.[Muhammad Ferjad], Xian, Y.Q.[Yong-Qin], Akata, Z.[Zeynep],
Learning Graph Embeddings for Open World Compositional Zero-Shot Learning,
PAMI(46), No. 3, March 2024, pp. 1545-1560.
IEEE DOI 2402
Visualization, Training, Standards, Task analysis, Dogs, Convolutional neural networks, Smoothing methods, scene understanding BibRef

Karthik, S.[Shyamgopal], Mancini, M.[Massimiliano], Akata, Z.[Zeynep],
KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning,
CVPR22(9326-9335)
IEEE DOI 2210
Training, Visualization, Image recognition, Computational modeling, Knowledge based systems, Semisupervised learning, Representation learning BibRef

Khan, M.G.Z.A.[Muhammad Gul Zain Ali], Naeem, M.F.[Muhammad Ferjad], Van Gool, L.J.[Luc J.], Pagani, A., Stricker, D.[Didier], Afzal, M.Z.[Muhammad Zeshan],
Learning Attention Propagation for Compositional Zero-Shot Learning,
WACV23(3817-3826)
IEEE DOI 2302
Training, Visualization, Buildings, Dogs, Bicycles, Benchmark testing, Algorithms: Image recognition and understanding (object detection, and un-supervised learning) BibRef

Naeem, M.F.[Muhammad Ferjad], Örnek, E.P.[Evin Pinar], Xian, Y.Q.[Yong-Qin], Van Gool, L.J.[Luc J.], Tombari, F.[Federico],
3D Compositional Zero-Shot Learning with DeCompositional Consensus,
ECCV22(XXVIII:713-730).
Springer DOI 2211
BibRef

Naeem, M.F.[Muhammad Ferjad], Xian, Y.Q.[Yong-Qin], Tombari, F.[Federico], Akata, Z.[Zeynep],
Learning Graph Embeddings for Compositional Zero-shot Learning,
CVPR21(953-962)
IEEE DOI 2111
Training, Visualization, Knowledge based systems, Semantics, Dogs, Benchmark testing BibRef

Mancini, M.[Massimiliano], Naeem, M.F.[Muhammad Ferjad], Xian, Y.Q.[Yong-Qin], Akata, Z.[Zeynep],
Open World Compositional Zero-Shot Learning,
CVPR21(5218-5226)
IEEE DOI 2111
Training, Degradation, Visualization, Computational modeling, Knowledge based systems, Benchmark testing BibRef

Ma, X.J.[Xing-Jiang], Yang, J.[Jing], Lin, J.C.[Jia-Cheng], Zheng, Z.Z.[Zhen-Zhe], Li, S.B.[Shao-Bo], Hu, B.Q.[Bing-Qi], Tang, X.H.[Xiang-Hong],
LVAR-CZSL: Learning Visual Attributes Representation for Compositional Zero-Shot Learning,
CirSysVideo(34), No. 12, December 2024, pp. 13311-13323.
IEEE DOI Code:
WWW Link. 2501
Visualization, Feature extraction, Dogs, Task analysis, Attention mechanisms, Zero-shot learning, inter-class connectivity BibRef

Zhang, T.[Tian], Liang, K.M.[Kong-Ming], Du, R.Y.[Ruo-Yi], Chen, W.[Wei], Ma, Z.Y.[Zhan-Yu],
Disentangling Before Composing: Learning Invariant Disentangled Features for Compositional Zero-Shot Learning,
PAMI(47), No. 2, February 2025, pp. 1132-1147.
IEEE DOI 2501
Training, Object oriented modeling, Zero shot learning, Visualization, Testing, Correlation, Data models, Training data, out-of-distribution generalization BibRef

Zhang, T.[Tian], Liang, K.M.[Kong-Ming], Du, R.Y.[Ruo-Yi], Sun, X.[Xian], Ma, Z.Y.[Zhan-Yu], Guo, J.[Jun],
Learning Invariant Visual Representations for Compositional Zero-Shot Learning,
ECCV22(XXIV:339-355).
Springer DOI 2211
BibRef

Jiang, C.Y.[Chen-Yi], Wang, S.D.[Shi-Dong], Long, Y.[Yang], Li, Z.C.[Ze-Chao], Zhang, H.F.[Hao-Feng], Shao, L.[Ling],
Imaginary-Connected Embedding in Complex Space for Unseen Attribute-Object Discrimination,
PAMI(47), No. 3, March 2025, pp. 1395-1413.
IEEE DOI 2502
Recognize novel compositions of primitives. Compositional. Visualization, Cognition, Prototypes, Semantics, Zero shot learning, Extraterrestrial measurements, Dogs, Training, Phase measurement, open-world classification BibRef

Min, L.T.[Ling-Tong], Fan, Z.[Ziman], Wang, S.Z.[Shun-Zhou], Dou, F.Y.[Fei-Yang], Li, X.[Xin], Wang, B.L.[Bing-Lu],
Adaptive Fusion Learning for Compositional Zero-Shot Recognition,
MultMed(27), 2025, pp. 1193-1204.
IEEE DOI 2503
Visualization, Training, Zero shot learning, Text recognition, Adaptation models, Accuracy, Transformers, Predictive models, visual encoder BibRef

Jiang, H.[Han], Chen, C.F.[Chao-Fan], Yang, X.S.[Xiao-Shan], Xu, C.S.[Chang-Sheng],
Compact Latent Primitive Space Learning for Compositional Zero-Shot Learning,
MultMed(27), 2025, pp. 4297-4308.
IEEE DOI 2507
Visualization, Zero shot learning, Encoding, Image reconstruction, Training, Semantics, Learning systems, Iris recognition, feature coding BibRef

Liu, Y.[Yang], Wang, X.[Xinshuo], Gao, X.B.[Xin-Bo], Han, J.G.[Jun-Gong], Shao, L.[Ling],
Multi-Level Contextual Prototype Modulation for Compositional Zero-Shot Learning,
IP(34), 2025, pp. 4856-4868.
IEEE DOI 2508
Visualization, Prototypes, Contrastive learning, Modulation, Training, Zero shot learning, Feature extraction, Transformers, data augmentation BibRef

Wang, Q.S.[Qing-Sheng], Liu, L.Q.[Ling-Qiao], Jing, C.C.[Chen-Chen], Wang, P.[Peng], Zhang, Y.N.[Yan-Ning], Shen, C.H.[Chun-Hua],
Learning Dual-Stream Conditional Concepts in Compositional Zero-Shot Learning,
PAMI(47), No. 11, November 2025, pp. 10076-10093.
IEEE DOI 2510
Visualization, Semantics, Image recognition, Zero shot learning, Streaming media, Dairy products, Feature extraction, zero-shot learning BibRef

Wang, Q.S.[Qing-Sheng], Liu, L.Q.[Ling-Qiao], Jing, C.C.[Chen-Chen], Chen, H.[Hao], Liang, G.Q.[Guo-Qiang], Wang, P.[Peng], Shen, C.H.[Chun-Hua],
Learning Conditional Attributes for Compositional Zero-Shot Learning,
CVPR23(11197-11206)
IEEE DOI 2309
BibRef

Chen, Z.[Ziyi], Zhao, X.[Xinru], Lang, C.Y.[Cong-Yan], Wei, L.[Lili], Wang, T.[Tao], Li, Y.D.[Yi-Dong],
Learning Diversified Primitive Prompts for Compositional Zero-Shot Learning,
CirSysVideo(35), No. 10, October 2025, pp. 10423-10436.
IEEE DOI 2510
Visualization, Training, Zero shot learning, Semantics, Image recognition, Large language models, joint-prompt learning BibRef

Deng, F.Q.[Fu-Qin], Tang, C.[Caiyun], Fu, L.[Lanhui], Jin, W.[Wei], Zhong, J.M.[Jia-Ming], Wang, H.M.[Hong-Ming], Li, N.N.[Nan-Nan],
GNN-based primitive recombination for compositional zero-shot learning,
IVC(163), 2025, pp. 105762.
Elsevier DOI 2511
Compositional zero-shot learning, Contrastive language-image pre-training, Graph neural network BibRef

Yu, X.W.[Xiao-Wei], Zhang, L.[Lu], Wu, Z.[Zihao], Zhu, D.J.[Da-Jiang],
Core-Periphery Multi-Modality Feature Alignment for Zero-Shot Medical Image Analysis,
MedImg(44), No. 10, October 2025, pp. 3973-3983.
IEEE DOI 2511
Biomedical imaging, Feature extraction, Biological neural networks, Contrastive learning, Diseases, Lung, brain-inspired AI BibRef

Jiang, H.[Han], Yang, X.S.[Xiao-Shan], Chen, C.F.[Chao-Fan], Xu, C.S.[Chang-Sheng],
SPDQ: Synergetic Prompts as Disentanglement Queries for Compositional Zero-Shot Learning,
MultMed(27), 2025, pp. 8888-8899.
IEEE DOI 2511
Visualization, Tuning, Adaptation models, Zero shot learning, Training, Artificial intelligence, Modulation, Data mining, prompt tuning BibRef


Wu, P.[Peng], Lu, X.[Xiankai], Hu, H.[Hao], Xian, Y.Q.[Yong-Qin], Shen, J.B.[Jian-Bing], Wang, W.G.[Wen-Guan],
LogiCzsl: Exploring Logic-induced Representation for Compositional Zero-shot Learning,
CVPR25(30301-30311)
IEEE DOI 2508
Training, Large language models, Semantics, Zero shot learning, Pipelines, Neural networks, Training data, Logic BibRef

Jiang, D.Y.[Dong-Yao], Jing, H.D.[Hao-Dong], Ma, Y.Q.[Yong-Qiang], Zheng, N.N.[Nan-Ning],
Beyond Image Classification: A Video Benchmark and Dual-Branch Hybrid Discrimination Framework for Compositional Zero-Shot Learning,
CVPR25(9860-9869)
IEEE DOI 2508
Visualization, Zero shot learning, Benchmark testing, Market research, Cognition, Robustness, Decoding, Videos, cross attention BibRef

Saini, N.[Nirat], Pham, K.[Khoi], Shrivastava, A.[Abhinav],
Beyond Seen Primitive Concepts and Attribute-Object Compositional Learning,
CVPR24(14466-14476)
IEEE DOI Code:
WWW Link. 2410
Vocabulary, Correlation, Zero-shot learning, Semantics, Benchmark testing, Open Vocabulary, Attributes of Objects BibRef

Bao, W.T.[Wen-Tao], Chen, L.[Lichang], Huang, H.[Heng], Kong, Y.[Yu],
Prompting Language-informed Distribution for Compositional Zero-Shot Learning,
ECCV24(XIV: 107-123).
Springer DOI 2412
BibRef

Shi, Y.Y.[Yu-Yan], Jiang, C.[Chenyi], Shi, R.[Run], Zhang, H.F.[Hao-Feng],
Do They Share the Same Tail? Learning Individual Compositional Attribute Prototype for Generalized Zero-shot Learning,
ACCV24(III: 239-256).
Springer DOI 2412
BibRef

Huang, S.T.[Si-Teng], Gong, B.[Biao], Feng, Y.T.[Yu-Tong], Zhang, M.[Min], Lv, Y.L.[Yi-Liang], Wang, D.L.[Dong-Lin],
Troika: Multi-Path Cross-Modal Traction for Compositional Zero-Shot Learning,
CVPR24(24005-24014)
IEEE DOI Code:
WWW Link. 2410
Visualization, Adaptation models, Limiting, Codes, Zero-shot learning, Benchmark testing, Troika BibRef

Zheng, Z.H.[Zhao-Heng], Zhu, H.D.[Hai-Dong], Nevatia, R.[Ram],
CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning,
WACV24(1710-1720)
IEEE DOI 2404
Adaptation models, Zero-shot learning, Semantics, Benchmark testing, Feature extraction, Vision + language and/or other modalities BibRef

Xu, G.Y.[Guang-Yue], Chai, J.[Joyce], Kordjamshidi, P.[Parisa],
GIPCOL: Graph-Injected Soft Prompting for Compositional Zero-Shot Learning,
WACV24(5762-5771)
IEEE DOI 2404
Training, Image recognition, Zero-shot learning, Computational modeling, Training data, Benchmark testing BibRef

Kim, H.[Hanjae], Lee, J.Y.[Ji-Young], Park, S.[Seongheon], Sohn, K.H.[Kwang-Hoon],
Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning,
ICCV23(5652-5662)
IEEE DOI Code:
WWW Link. 2401
BibRef

Lu, X.C.[Xiao-Cheng], Guo, S.[Song], Liu, Z.M.[Zi-Ming], Guo, J.C.[Jing-Cai],
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot Learning,
CVPR23(23560-23569)
IEEE DOI 2309
BibRef

Hao, S.Z.[Shao-Zhe], Han, K.[Kai], Wong, K.Y.K.[Kwan-Yee K.],
Learning Attention as Disentangler for Compositional Zero-Shot Learning,
CVPR23(15315-15324)
IEEE DOI 2309
BibRef

Li, Y.[Yun], Liu, Z.[Zhe], Jha, S.[Saurav], Yao, L.[Lina],
Distilled Reverse Attention Network for Open-world Compositional Zero-Shot Learning,
ICCV23(1782-1791)
IEEE DOI 2401
BibRef

Panda, A.[Aditya], Santra, B.[Bikash], Mukherjee, D.P.[Dipti Prasad],
Bi-Modal Compositional Network for Feature Disentanglement,
ICIP22(3051-3055)
IEEE DOI 2211
New compositions of known objects. Visualization, Benchmark testing, Object recognition, composition, disentanglement, CZSL, state-object composition, compositional zero shot 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

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Zero-Shot Learning for Vision Transformers .


Last update:Nov 26, 2025 at 20:24:09