SOTAVerified

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

Showing 1120 of 161 papers

TitleStatusHype
Generative Zero-Shot Learning for Semantic Segmentation of 3D Point CloudsCode1
FREE: Feature Refinement for Generalized Zero-Shot LearningCode1
Multi-Label Generalized Zero Shot Learning for the Classification of Disease in Chest RadiographsCode1
Contrastive Embedding for Generalized Zero-Shot LearningCode1
Goal-Oriented Gaze Estimation for Zero-Shot LearningCode1
Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action RecognitionCode1
Semantics Disentangling for Generalized Zero-Shot LearningCode1
Adaptive and Generative Zero-Shot LearningCode1
A Review of Generalized Zero-Shot Learning MethodsCode1
Generalized Zero-Shot Learning via VAE-Conditioned Generative FlowCode1
Show:102550
← PrevPage 2 of 17Next →

No leaderboard results yet.