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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 131–140 of 161 papers

Title	Date	Tasks	Status
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders	Jun 1, 2019	Few-Shot LearningGeneralized Few-Shot Learning	CodeCode Available
Mitigating Generation Shifts for Generalized Zero-Shot Learning	Jul 7, 2021	AttributeGeneralized Zero-Shot Learning	CodeCode Available
Zero-shot Word Sense Disambiguation using Sense Definition Embeddings	Jul 1, 2019	Generalized Zero-Shot LearningGraph Embedding	CodeCode Available
Online Lifelong Generalized Zero-Shot Learning	Mar 19, 2021	Continual LearningGeneralized Zero-Shot Learning	CodeCode Available
Deconstructed Generation-Based Zero-Shot Model	Apr 24, 2022	AttributeGeneralized Zero-Shot Learning	CodeCode Available
Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance	Aug 8, 2018	Generalized Zero-Shot LearningZero-Shot Learning	CodeCode Available
Multi-modal Cycle-consistent Generalized Zero-Shot Learning	Aug 1, 2018	General ClassificationGeneralized Zero-Shot Learning	CodeCode Available
Alleviating Feature Confusion for Generative Zero-shot Learning	Sep 17, 2019	Generalized Zero-Shot LearningZero-Shot Learning	CodeCode Available
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders	Dec 5, 2018	Few-Shot LearningGeneralized Few-Shot Learning	CodeCode Available
Evolutionary Generalized Zero-Shot Learning	Nov 23, 2022	AttributeGeneralized Zero-Shot Learning	CodeCode Available

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