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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 76–100 of 161 papers

TitleStatusHype
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning—0
Bridging the Projection Gap: Overcoming Projection Bias Through Parameterized Distance Learning—0
Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects—0
Model Selection for Generalized Zero-shot Learning—0
Multi-Knowledge Fusion for New Feature Generation in Generalized Zero-Shot Learning—0
Multi-modal Ensemble Classification for Generalized Zero Shot Learning—0
Multimodal Generalized Zero Shot Learning for Gleason Grading using Self-Supervised Learning—0
Multiple-Input Multiple-Output Fusion Network For Generalized Zero-Shot Learning—0
Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis—0
Prototypical Model with Novel Information-theoretic Loss Function for Generalized Zero Shot Learning—0
PSVMA+: Exploring Multi-granularity Semantic-visual Adaption for Generalized Zero-shot Learning—0
Rectification-based Knowledge Retention for Continual Learning—0
Relation-based Generalized Zero-shot Classification with the Domain Discriminator on the shared representation—0
RevCD -- Reversed Conditional Diffusion for Generalized Zero-Shot Learning—0
SEER-ZSL: Semantic Encoder-Enhanced Representations for Generalized Zero-Shot Learning—0
Self-Supervised Domain-Aware Generative Network for Generalized Zero-Shot Learning—0
Progressive Ensemble Networks for Zero-Shot Recognition—0
Semantic Borrowing for Generalized Zero-Shot Learning—0
Semantic-diversity transfer network for generalized zero-shot learning via inner disagreement based OOD detector—0
Semantic Feature Extraction for Generalized Zero-shot Learning—0
SDM-Net: A Simple and Effective Model for Generalized Zero-Shot Learning—0
Synthetic Sample Selection for Generalized Zero-Shot Learning—0
Targeted Attention for Generalized- and Zero-Shot Learning—0
Task Aligned Generative Meta-learning for Zero-shot Learning—0
Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning—0
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