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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
Zero-Shot Learning by Harnessing Adversarial SamplesCode0
Improving Zero-Shot Generalization for CLIP with Synthesized PromptsCode1
Synthetic Sample Selection for Generalized Zero-Shot Learning—0
Progressive Semantic-Visual Mutual Adaption for Generalized Zero-Shot LearningCode1
Zero-Knowledge Zero-Shot Learning for Novel Visual Category Discovery—0
Vision Transformer-based Feature Extraction for Generalized Zero-Shot Learning—0
Learning Generalized Zero-Shot Learners for Open-Domain Image GeolocalizationCode0
Evolutionary Generalized Zero-Shot LearningCode0
On the Transferability of Visual Features in Generalized Zero-Shot LearningCode0
Targeted Attention for Generalized- and Zero-Shot Learning—0
Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning—0
I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification—0
LETS-GZSL: A Latent Embedding Model for Time Series Generalized Zero Shot Learning—0
GSMFlow: Generation Shifts Mitigating Flow for Generalized Zero-Shot Learning—0
PROTOtypical Logic Tensor Networks (PROTO-LTN) for Zero Shot LearningCode0
Recognition of Unseen Bird Species by Learning from Field GuidesCode0
Learn to Adapt for Generalized Zero-Shot Text ClassificationCode1
Zero-Shot Logit AdjustmentCode1
Deconstructed Generation-Based Zero-Shot ModelCode0
Interpretable Saliency Maps And Self-Supervised Learning For Generalized Zero Shot Medical Image Classification—0
Unseen Classes at a Later Time? No ProblemCode1
Semantic-diversity transfer network for generalized zero-shot learning via inner disagreement based OOD detector—0
Non-generative Generalized Zero-shot Learning via Task-correlated Disentanglement and Controllable Samples Synthesis—0
A Gating Model for Bias Calibration in Generalized Zero-shot LearningCode0
Cluster-based Contrastive Disentangling for Generalized Zero-Shot Learning—0
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