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Generalized Zero-Shot Learning

In generalized zero shot learning (GZSL), the set of classes are split into seen and unseen classes, where training relies on the semantic features of the seen and unseen classes and the visual representations of only the seen classes, while testing uses the visual representations of the seen and unseen classes.

Papers

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Showing 26–50 of 161 papers

TitleStatusHype
Domain-aware Visual Bias Eliminating for Generalized Zero-Shot LearningCode1
Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal ModelsCode1
Improving Zero-Shot Generalization for CLIP with Synthesized PromptsCode1
Generalized Zero-Shot Learning via VAE-Conditioned Generative FlowCode1
Cluster-based Contrastive Disentangling for Generalized Zero-Shot Learning—0
A Prototype-Based Generalized Zero-Shot Learning Framework for Hand Gesture Recognition—0
Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders—0
Zero-Shot Recognition via Optimal Transport—0
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition—0
A Generalized Zero-Shot Framework for Emotion Recognition from Body Gestures—0
Generalized Zero-shot ICD Coding—0
CICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification—0
Integrated Generalized Zero-Shot Learning for Fine-Grained Classification—0
An Entropy-guided Reinforced Partial Convolutional Network for Zero-Shot Learning—0
Entropy-Based Uncertainty Calibration for Generalized Zero-Shot Learning—0
En-Compactness: Self-Distillation Embedding & Contrastive Generation for Generalized Zero-Shot Learning—0
Bidirectional Mapping Coupled GAN for Generalized Zero-Shot Learning—0
Generalized Zero-Shot Classification via Semantics-Free Inter-Class Feature Generation—0
Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data—0
Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning—0
Dual Progressive Prototype Network for Generalized Zero-Shot Learning—0
CLAREL: Classification via retrieval loss for zero-shot learning—0
Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning—0
AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings—0
Fine-Grained Generalized Zero-Shot Learning via Dense Attribute-Based Attention—0
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