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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 101–150 of 161 papers

TitleStatusHype
A Boundary Based Out-of-Distribution Classifier for Generalized Zero-Shot LearningCode1
Generalized Zero-Shot Domain Adaptation via Coupled Conditional Variational Autoencoders—0
Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot LearningCode1
Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-shot Learning—0
Class Normalization for (Continual)? Generalized Zero-Shot LearningCode1
Zero-Shot Learning with Common Sense Knowledge GraphsCode1
Learning the Redundancy-free Features for Generalized Zero-Shot Object Recognition—0
Fine-Grained Generalized Zero-Shot Learning via Dense Attribute-Based Attention—0
Self-Supervised Domain-Aware Generative Network for Generalized Zero-Shot Learning—0
Improving Generalized Zero-Shot Learning by Semantic Discriminator—0
AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings—0
From Generalized zero-shot learning to long-tail with class descriptorsCode1
Generalized Zero-Shot Learning Via Over-Complete DistributionCode0
Domain-aware Visual Bias Eliminating for Generalized Zero-Shot LearningCode1
Latent Embedding Feedback and Discriminative Features for Zero-Shot ClassificationCode1
Domain segmentation and adjustment for generalized zero-shot learning—0
Transductive Zero-Shot Learning for 3D Point Cloud ClassificationCode1
Heterogeneous Graph-based Knowledge Transfer for Generalized Zero-shot Learning—0
Zero-Shot Recognition via Optimal Transport—0
Generalized Zero-shot ICD Coding—0
Relation-based Generalized Zero-shot Classification with the Domain Discriminator on the shared representation—0
Alleviating Feature Confusion for Generative Zero-shot LearningCode0
A Meta-Learning Framework for Generalized Zero-Shot LearningCode0
SDM-Net: A Simple and Effective Model for Generalized Zero-Shot Learning—0
Transferable Contrastive Network for Generalized Zero-Shot Learning—0
Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning—0
Discriminative Embedding Autoencoder with a Regressor Feedback for Zero-Shot Learning—0
Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects—0
Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning—0
Zero-shot Word Sense Disambiguation using Sense Definition EmbeddingsCode0
Hierarchical Disentanglement of Discriminative Latent Features for Zero-Shot Learning—0
Compressing Unknown Images With Product Quantizer for Efficient Zero-Shot Classification—0
Generalized Zero- and Few-Shot Learning via Aligned Variational AutoencodersCode0
CLAREL: Classification via retrieval loss for zero-shot learning—0
Learning shared manifold representation of images and attributes for generalized zero-shot learning—0
Leveraging the Invariant Side of Generative Zero-Shot LearningCode0
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning—0
Unifying Unsupervised Domain Adaptation and Zero-Shot Visual RecognitionCode0
Cross-Linked Variational Autoencoders for Generalized Zero-Shot Learning—0
Multi-modal Ensemble Classification for Generalized Zero Shot Learning—0
Adaptive Confidence Smoothing for Generalized Zero-Shot Learning—0
Generalized Zero- and Few-Shot Learning via Aligned Variational AutoencodersCode0
Generalized Zero-Shot Learning with Deep Calibration Network—0
Generalized Zero-Shot Recognition based on Visually Semantic Embedding—0
Generative Dual Adversarial Network for Generalized Zero-shot LearningCode0
Model Selection for Generalized Zero-shot Learning—0
Learning the Compositional Spaces for Generalized Zero-shot Learning—0
Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features—0
From Classical to Generalized Zero-Shot Learning: a Simple Adaptation Process—0
Choose Your Neuron: Incorporating Domain Knowledge through Neuron-ImportanceCode0
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