Data to 7 Oct 2026

Attribute Prototype Network for Zero-Shot Learning

arXiv 2008.08290 ↗First posted 19 Aug 2020cs.CV cs.LGcited by 160

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Abstract (arXiv)

From the beginning of zero-shot learning research, visual attributes have been shown to play an important role. In order to better transfer attribute-based knowledge from known to unknown classes, we argue that an image representation with integrated attribute localization ability would be beneficial for zero-shot learning. To this end, we propose a novel zero-shot representation learning framework that jointly learns discriminative global and local features using only class-level attributes. While a visual-semantic embedding layer learns global features, local features are learned through an attribute prototype network that simultaneously regresses and decorrelates attributes from intermediate features. We show that our locality augmented image representations achieve a new state-of-the-art on three zero-shot learning benchmarks. As an additional benefit, our model points to the visual evidence of the attributes in an image, e.g. for the CUB dataset, confirming the improved attribute localization ability of our image representation.

Key facts. Cited by 160 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Aug 2020.

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Citing papers per year: 2021: 26; 2022: 33; 2023: 29; 2024: 41; 2025: 25; 2026: 6.

160 papers.

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2022Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classificationcited by 310
2022Rethinking Semantic Segmentation: A Prototype Viewcited by 140
2024OneRestore: A Universal Restoration Framework for Composite Degradationcited by 91
2021Goal-Oriented Gaze Estimation for Zero-Shot Learningcited by 68
2021This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networkscited by 65
2022Visual Recognition with Deep Nearest Centroidscited by 59
2021HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learningcited by 57
2022I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classificationcited by 54
2021TransZero: Attribute-guided Transformer for Zero-Shot Learningcited by 53
2023Improving Zero-Shot Generalization for CLIP with Synthesized Promptscited by 51
2022MSDN: Mutually Semantic Distillation Network for Zero-Shot Learningcited by 48
2024FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learningcited by 47

38 more

2021Zero-Shot Recommender Systemscited by 45
2023OvarNet: Towards Open-vocabulary Object Attribute Recognitioncited by 43
2021Independent Prototype Propagation for Zero-Shot Compositionalitycited by 42
2021Hyperbolic Busemann Learning with Ideal Prototypescited by 40
2022DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learningcited by 33
2022On Guiding Visual Attention with Language Specificationcited by 30
2021TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learningcited by 28
2022Open-vocabulary Attribute Detectioncited by 28
2022Audio-visual Generalised Zero-shot Learning with Cross-modal Attention and Languagecited by 27
2022VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learningcited by 27
2022I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classificationcited by 27
2023Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanationscited by 27
2021Dual Progressive Prototype Network for Generalized Zero-Shot Learningcited by 26
2023TENT: Connect Language Models with IoT Sensors for Zero-Shot Activity Recognitioncited by 25
2021Semantic Diversity Learning for Zero-Shot Multi-label Classificationcited by 24
2023Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot Learningcited by 24
2023Zero-Shot Learning by Harnessing Adversarial Samplescited by 24
2022PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learningcited by 21
2024Cross-Modal Prototype based Multimodal Federated Learning under Severely Missing Modalitycited by 21
2021Human Attention in Fine-grained Classificationcited by 20
2022Hybrid Routing Transformer for Zero-Shot Learningcited by 20
2023Evolving Semantic Prototype Improves Generative Zero-Shot Learningcited by 20
2022Attribute Prototype Network for Any-Shot Learningcited by 19
2022Temporal and cross-modal attention for audio-visual zero-shot learningcited by 19
2024Progressive Semantic-Guided Vision Transformer for Zero-Shot Learningcited by 17
2024COMAE: COMprehensive Attribute Exploration for Zero-shot Hashingcited by 16
2024Hunting Attributes: Context Prototype-Aware Learning for Weakly Supervised Semantic Segmentationcited by 16
2024Visual-Augmented Dynamic Semantic Prototype for Generative Zero-Shot Learningcited by 16
2021Zero-shot Node Classification with Decomposed Graph Prototype Networkcited by 15
2022COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentationcited by 15
2023Image-free Classifier Injection for Zero-Shot Classificationcited by 15
2023Simple Image-level Classification Improves Open-vocabulary Object Detectioncited by 15
2024AAPL: Adding Attributes to Prompt Learning for Vision-Language Modelscited by 14
2021Detecting Anomalies in Semantic Segmentation with Prototypescited by 13
2025Learning Clustering-based Prototypes for Compositional Zero-shot Learningcited by 13
2021Multi-Head Self-Attention via Vision Transformer for Zero-Shot Learningcited by 12
2024Fine-Grained Zero-Shot Learning: Advances, Challenges, and Prospectscited by 12
2024CREST: Cross-modal Resonance through Evidential Deep Learning for Enhanced Zero-Shot Learningcited by 12

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