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Generalized Zero-Shot Learning via Synthesized Examples

arXiv 1712.03878 ↗First posted 11 Dec 2017cs.LG cs.CV stat.MLcited by 114

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Abstract (arXiv)

We present a generative framework for generalized zero-shot learning where the training and test classes are not necessarily disjoint. Built upon a variational autoencoder based architecture, consisting of a probabilistic encoder and a probabilistic conditional decoder, our model can generate novel exemplars from seen/unseen classes, given their respective class attributes. These exemplars can subsequently be used to train any off-the-shelf classification model. One of the key aspects of our encoder-decoder architecture is a feedback-driven mechanism in which a discriminator (a multivariate regressor) learns to map the generated exemplars to the corresponding class attribute vectors, leading to an improved generator. Our model's ability to generate and leverage examples from unseen classes to train the classification model naturally helps to mitigate the bias towards predicting seen classes in generalized zero-shot learning settings. Through a comprehensive set of experiments, we show that our model outperforms several state-of-the-art methods, on several benchmark datasets, for both standard as well as generalized zero-shot learning.

Key facts. Cited by 114 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Dec 2017.

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Citing papers per year: 2018: 1; 2019: 0; 2020: 0; 2021: 48; 2022: 27; 2023: 18; 2024: 13; 2025: 5; 2026: 2.

114 papers.

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  1. 2021Contrastive Embedding for Generalized Zero-Shot Learningcited by 94
  2. 2021Domain Impression: A Source Data Free Domain Adaptation Methodcited by 91
  3. 2021Detecting Human-Object Interaction via Fabricated Compositional Learningcited by 79
  4. 2021Goal-Oriented Gaze Estimation for Zero-Shot Learningcited by 68
  5. 2021FREE: Feature Refinement for Generalized Zero-Shot Learningcited by 67
  6. 2022Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Featurescited by 63
  7. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  8. 2021Semantics Disentangling for Generalized Zero-Shot Learningcited by 56
  9. 2021Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Cloudscited by 55
  10. 2021TransZero: Attribute-guided Transformer for Zero-Shot Learningcited by 54
  11. 2022I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classificationcited by 54
  12. 2022MSDN: Mutually Semantic Distillation Network for Zero-Shot Learningcited by 48
38 more
  1. 2021Zero-Shot Instance Segmentationcited by 40
  2. 2022Generating Representative Samples for Few-Shot Classificationcited by 39
  3. 2021A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representationscited by 37
  4. 2022Zero-shot object goal visual navigationcited by 31
  5. 2021TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learningcited by 28
  6. 2022Audio-visual Generalised Zero-shot Learning with Cross-modal Attention and Languagecited by 27
  7. 2022I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classificationcited by 27
  8. 2021Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognitioncited by 24
  9. 2021Fine-Grained Zero-Shot Learning with DNA as Side Informationcited by 20
  10. 2022Robust Region Feature Synthesizer for Zero-Shot Object Detectioncited by 20
  11. 2022Hybrid Routing Transformer for Zero-Shot Learningcited by 20
  12. 2023Evolving Semantic Prototype Improves Generative Zero-Shot Learningcited by 20
  13. 2021Task Aligned Generative Meta-learning for Zero-shot Learningcited by 19
  14. 2022Attribute Prototype Network for Any-Shot Learningcited by 19
  15. 2021Learning Robust Visual-semantic Mapping for Zero-shot Learningcited by 16
  16. 2021Learning from Multiple Noisy Partial Labelerscited by 14
  17. 2021A New Split for Evaluating True Zero-Shot Action Recognitioncited by 14
  18. 2022Zero-Shot AutoML with Pretrained Modelscited by 14
  19. 2023Synthetic Sample Selection for Generalized Zero-Shot Learningcited by 14
  20. 2024Long-Tailed Anomaly Detection with Learnable Class Namescited by 14
  21. 2024CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot Learningcited by 12
  22. 2023Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open Worldscited by 11
  23. 2025Logits DeConfusion with CLIP for Few-Shot Learningcited by 11
  24. 2024Spiking Tucker Fusion Transformer for Audio-Visual Zero-Shot Learningcited by 10
  25. 2021CrossATNet - A Novel Cross-Attention Based Framework for Sketch-Based Image Retrievalcited by 9
  26. 2021Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learningcited by 8
  27. 2022Boosting Zero-shot Learning via Contrastive Optimization of Attribute Representationscited by 8
  28. 2021Generative Replay-based Continual Zero-Shot Learningcited by 7
  29. 2021Deep Model Compression based on the Training Historycited by 7
  30. 2021CIZSL++: Creativity Inspired Generative Zero-Shot Learningcited by 6
  31. 2021Region Semantically Aligned Network for Zero-Shot Learningcited by 6
  32. 2022How Robust are Discriminatively Trained Zero-Shot Learning Models?cited by 6
  33. 2022A Gating Model for Bias Calibration in Generalized Zero-shot Learningcited by 6
  34. 2023EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learningcited by 6
  35. 2023Attribute-Aware Representation Rectification for Generalized Zero-Shot Learningcited by 6
  36. 2021Cross Knowledge-based Generative Zero-Shot Learning Approach with Taxonomy Regularizationcited by 5
  37. 2021SAC-GAN: Structure-Aware Image Compositioncited by 5
  38. 2024On the Element-Wise Representation and Reasoning in Zero-Shot Image Recognition: A Systematic Surveycited by 5

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