mlsanityData to 14 Oct 2026

Visual and Semantic Prompt Collaboration for Generalized Zero-Shot Learning

arXiv 2503.23030 ↗First posted 29 Mar 2025cs.CVcited by 4

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Abstract (arXiv)

Generalized zero-shot learning aims to recognize both seen and unseen classes with the help of semantic information that is shared among different classes. It inevitably requires consistent visual-semantic alignment. Existing approaches fine-tune the visual backbone by seen-class data to obtain semantic-related visual features, which may cause overfitting on seen classes with a limited number of training images. This paper proposes a novel visual and semantic prompt collaboration framework, which utilizes prompt tuning techniques for efficient feature adaptation. Specifically, we design a visual prompt to integrate the visual information for discriminative feature learning and a semantic prompt to integrate the semantic formation for visualsemantic alignment. To achieve effective prompt information integration, we further design a weak prompt fusion mechanism for the shallow layers and a strong prompt fusion mechanism for the deep layers in the network. Through the collaboration of visual and semantic prompts, we can obtain discriminative semantic-related features for generalized zero-shot image recognition. Extensive experiments demonstrate that our framework consistently achieves favorable performance in both conventional zero-shot learning and generalized zero-shot learning benchmarks compared to other state-of-the-art methods.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 40 of its 66 references that are in the map. First posted on arXiv 29 Mar 2025.

Builds on

40 of 66 references.

References · 40

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2021Learning to Prompt for Continual Learningcited by 944
  4. 2022DualPrompt: Complementary Prompting for Rehearsal-free Continual Learningcited by 642
  5. 2017Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad and the Uglycited by 538
  6. 2017Feature Generating Networks for Zero-Shot Learningcited by 257
  7. 2016Learning Deep Representations of Fine-grained Visual Descriptionscited by 182
  8. 2020Attribute Prototype Network for Zero-Shot Learningcited by 160
  9. 2018Zero-shot Recognition via Semantic Embeddings and Knowledge Graphscited by 155
  10. 2016Learning a Deep Embedding Model for Zero-Shot Learningcited by 153
  11. 2023Text-to-Image Diffusion Models are Zero-Shot Classifierscited by 143
  12. 2016Latent Embeddings for Zero-shot Classificationcited by 129
28 more
  1. 2017Generalized Zero-Shot Learning via Synthesized Examplescited by 114
  2. 2021Contrastive Embedding for Generalized Zero-Shot Learningcited by 94
  3. 2019Leveraging the Invariant Side of Generative Zero-Shot Learningcited by 83
  4. 2021Goal-Oriented Gaze Estimation for Zero-Shot Learningcited by 68
  5. 2021FREE: Feature Refinement for Generalized Zero-Shot Learningcited by 67
  6. 2022Learning to Compose Soft Prompts for Compositional Zero-Shot Learningcited by 67
  7. 2015Predicting Deep Zero-Shot Convolutional Neural Networks using Textual Descriptionscited by 64
  8. 2019Transferable Contrastive Network for Generalized Zero-Shot Learningcited by 64
  9. 2020Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot Learningcited by 64
  10. 2019Semantic-Guided Multi-Attention Localization for Zero-Shot Learningcited by 58
  11. 2021HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learningcited by 57
  12. 2021TransZero: Attribute-guided Transformer for Zero-Shot Learningcited by 54
  13. 2022MSDN: Mutually Semantic Distillation Network for Zero-Shot Learningcited by 48
  14. 2018Transductive Unbiased Embedding for Zero-Shot Learningcited by 44
  15. 2022DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learningcited by 33
  16. 2023Semantic Prompt for Few-Shot Image Recognitioncited by 29
  17. 2021Dual Progressive Prototype Network for Generalized Zero-Shot Learningcited by 26
  18. 2023Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot Learningcited by 24
  19. 2021Generative Multi-Label Zero-Shot Learningcited by 19
  20. 2024Progressive Semantic-Guided Vision Transformer for Zero-Shot Learningcited by 17
  21. 2024Visual-Augmented Dynamic Semantic Prototype for Generative Zero-Shot Learningcited by 16
  22. 2023Image-free Classifier Injection for Zero-Shot Classificationcited by 15
  23. 2017Semantically Consistent Regularization for Zero-Shot Recognitioncited by 14
  24. 2018Learning Class Prototypes via Structure Alignment for Zero-Shot Recognitioncited by 14
  25. 2021Multi-Head Self-Attention via Vision Transformer for Zero-Shot Learningcited by 12
  26. 2022Meta-Learning via Classifier(-free) Diffusion Guidancecited by 9
  27. 2022Deconstructed Generation-Based Zero-Shot Modelcited by 6
  28. 2021Implicit and Explicit Attention for Zero-Shot Learningcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samplescited by 3
  2. 2025Fine-Grained Zero-Shot Learning with Attribute-Centric Representationscited by 0
  3. 2026Learning Adaptive and Visually Aligned Conditions for Generative Zero-Shot Learningcited by 0
  4. 2026Incentivizing Generative Zero-Shot Learning via Outcome-Reward Reinforcement Learning with Visual Cuescited by 0