mlsanityData to 7 Oct 2026

Latent Embeddings for Zero-shot Classification

arXiv 1603.08895 ↗First posted 29 Mar 2016cs.CVcited by 129

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Abstract (arXiv)

We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero-shot classification. The proposed method augments the state-of-the-art bilinear compatibility model by incorporating latent variables. Instead of learning a single bilinear map, it learns a collection of maps with the selection, of which map to use, being a latent variable for the current image-class pair. We train the model with a ranking based objective function which penalizes incorrect rankings of the true class for a given image. We empirically demonstrate that our model improves the state-of-the-art for various class embeddings consistently on three challenging publicly available datasets for the zero-shot setting. Moreover, our method leads to visually highly interpretable results with clear clusters of different fine-grained object properties that correspond to different latent variable maps.

Key facts. Cited by 129 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Mar 2016.

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Citing papers per year: 2021: 58; 2022: 31; 2023: 23; 2024: 8; 2025: 6; 2026: 3.

129 papers.

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  1. 2021PointCLIP: Point Cloud Understanding by CLIPcited by 461
  2. 2021A Simple Baseline for Open-Vocabulary Semantic Segmentation with Pre-trained Vision-language Modelcited by 223
  3. 2022Unified Contrastive Learning in Image-Text-Label Spacecited by 194
  4. 2021Combined Scaling for Zero-shot Transfer Learningcited by 182
  5. 2023CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIPcited by 178
  6. 2023Towards Open Vocabulary Learning: A Surveycited by 165
  7. 2021Semantic-aware Knowledge Distillation for Few-Shot Class-Incremental Learningcited by 114
  8. 2021Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representationscited by 96
  9. 2021Counterfactual Zero-Shot and Open-Set Visual Recognitioncited by 95
  10. 2021Contrastive Embedding for Generalized Zero-Shot Learningcited by 94
  11. 2023Vision-Language Models in Remote Sensing: Current Progress and Future Trendscited by 93
  12. 2022Deep Hierarchical Semantic Segmentationcited by 84
38 more
  1. 2021Goal-Oriented Gaze Estimation for Zero-Shot Learningcited by 68
  2. 2021FREE: Feature Refinement for Generalized Zero-Shot Learningcited by 67
  3. 2022Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Featurescited by 63
  4. 2021A Closer Look at Self-training for Zero-Label Semantic Segmentationcited by 57
  5. 2023Zero-shot Object Countingcited by 57
  6. 2021Semantics Disentangling for Generalized Zero-Shot Learningcited by 56
  7. 2021Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Cloudscited by 55
  8. 2022I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classificationcited by 54
  9. 2021SIGN: Spatial-information Incorporated Generative Network for Generalized Zero-shot Semantic Segmentationcited by 41
  10. 2023CLIP in Medical Imaging: A Surveycited by 40
  11. 2021Zero-Shot Learning on 3D Point Cloud Objects and Beyondcited by 38
  12. 2023Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentationcited by 29
  13. 2022VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learningcited by 27
  14. 2022I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classificationcited by 27
  15. 2021Semantics-Guided Contrastive Network for Zero-Shot Object detectioncited by 26
  16. 2021Dual Progressive Prototype Network for Generalized Zero-Shot Learningcited by 26
  17. 2021Semantic Diversity Learning for Zero-Shot Multi-label Classificationcited by 24
  18. 2023Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot Learningcited by 24
  19. 2023Language-Driven Anchors for Zero-Shot Adversarial Robustnesscited by 23
  20. 2021No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networkscited by 21
  21. 2022Towards Unbiased Multi-label Zero-Shot Learning with Pyramid and Semantic Attentioncited by 21
  22. 2023See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Datacited by 21
  23. 2021Fine-Grained Zero-Shot Learning with DNA as Side Informationcited by 20
  24. 2022Robust Region Feature Synthesizer for Zero-Shot Object Detectioncited by 20
  25. 2022Hybrid Routing Transformer for Zero-Shot Learningcited by 20
  26. 2021Task Aligned Generative Meta-learning for Zero-shot Learningcited by 19
  27. 2022Attribute Prototype Network for Any-Shot Learningcited by 19
  28. 2021Learning Robust Visual-semantic Mapping for Zero-shot Learningcited by 16
  29. 2024Scene Graph Generation with Role-Playing Large Language Modelscited by 16
  30. 2023Image-free Classifier Injection for Zero-Shot Classificationcited by 15
  31. 2021Learning from Multiple Noisy Partial Labelerscited by 14
  32. 2021A New Split for Evaluating True Zero-Shot Action Recognitioncited by 14
  33. 2024AAPL: Adding Attributes to Prompt Learning for Vision-Language Modelscited by 14
  34. 2021Mitigating Generation Shifts for Generalized Zero-Shot Learningcited by 13
  35. 2022Prefix Conditioning Unifies Language and Label Supervisioncited by 13
  36. 2023Multimodal Foundation Models for Zero-shot Animal Species Recognition in Camera Trap Imagescited by 13
  37. 2021Hardness Sampling for Self-Training Based Transductive Zero-Shot Learningcited by 12
  38. 2021Multi-Head Self-Attention via Vision Transformer for Zero-Shot Learningcited by 12

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