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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 101–125 of 161 papers

TitleStatusHype
Transferable Contrastive Network for Generalized Zero-Shot Learning—0
Using Fictitious Class Representations to Boost Discriminative Zero-Shot Learners—0
Vision Transformer-based Feature Extraction for Generalized Zero-Shot Learning—0
Visual and Semantic Prompt Collaboration for Generalized Zero-Shot Learning—0
Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning—0
Zero-Knowledge Zero-Shot Learning for Novel Visual Category Discovery—0
Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features—0
Zero-shot Learning via Shared-Reconstruction-Graph Pursuit—0
Global Semantic Consistency for Zero-Shot Learning—0
GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning—0
Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning—0
Hierarchical Disentanglement of Discriminative Latent Features for Zero-Shot Learning—0
Hierarchical Novelty Detection for Visual Object Recognition—0
High-Discriminative Attribute Feature Learning for Generalized Zero-Shot Learning—0
I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification—0
Improving Generalized Zero-Shot Learning by Semantic Discriminator—0
Instance Adaptive Prototypical Contrastive Embedding for Generalized Zero Shot Learning—0
Isometric Propagation Network for Generalized Zero-shot Learning—0
Learn from Anywhere: Rethinking Generalized Zero-Shot Learning with Limited Supervision—0
Learning Graph-Based Priors for Generalized Zero-Shot Learning—0
Learning shared manifold representation of images and attributes for generalized zero-shot learning—0
Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognition—0
Learning the Compositional Spaces for Generalized Zero-shot Learning—0
Learning Unseen Emotions from Gestures via Semantically-Conditioned Zero-Shot Perception with Adversarial Autoencoders—0
Learning without Seeing nor Knowing: Towards Open Zero-Shot Learning—0
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