Browse > Methodology > Zero-Shot Learning > Generalized Zero-Shot Learning

Generalized Zero-Shot Learning

13 papers with code ยท Methodology
Subtask of Zero-Shot Learning

State-of-the-art leaderboards

Trend Dataset Best Method Paper title Paper Code Compare

Latest papers without code

A Meta-Learning Framework for Generalized Zero-Shot Learning

10 Sep 2019

Our proposed model yields significant improvements on standard ZSL as well as more challenging GZSL setting.

GENERALIZED ZERO-SHOT LEARNING META-LEARNING

Transferable Contrastive Network for Generalized Zero-Shot Learning

16 Aug 2019

Zero-shot learning (ZSL) is a challenging problem that aims to recognize the target categories without seen data, where semantic information is leveraged to transfer knowledge from some source classes.

GENERALIZED ZERO-SHOT LEARNING TRANSFER LEARNING

Visual and Semantic Prototypes-Jointly Guided CNN for Generalized Zero-shot Learning

12 Aug 2019

On the other hand, for G-OSR, introducing such semantic information of known classes not only improves the recognition performance but also endows OSR with the cognitive ability of unknown classes.

GENERALIZED ZERO-SHOT LEARNING OPEN SET LEARNING

Discriminative Embedding Autoencoder with a Regressor Feedback for Zero-Shot Learning

18 Jul 2019

Zero-shot learning (ZSL) aims to recognize the novel object categories using the semantic representation of categories, and the key idea is to explore the knowledge of how the novel class is semantically related to the familiar classes.

GENERALIZED ZERO-SHOT LEARNING OBJECT RECOGNITION

Mitigating the Hubness Problem for Zero-Shot Learning of 3D Objects

15 Jul 2019

In this paper, we therefore propose a loss to specifically address the hubness problem.

3D OBJECT RECOGNITION GENERALIZED ZERO-SHOT LEARNING

Dual Adversarial Semantics-Consistent Network for Generalized Zero-Shot Learning

12 Jul 2019

In particular, the primal GAN learns to synthesize inter-class discriminative and semantics-preserving visual features from both the semantic representations of seen/unseen classes and the ones reconstructed by the dual GAN.

GENERALIZED ZERO-SHOT LEARNING TRANSFER LEARNING

Generative Dual Adversarial Network for Generalized Zero-Shot Learning

CVPR 2019

This paper studies the problem of generalized zero-shot learning which requires the model to train on image-label pairs from some seen classes and test on the task of classifying new images from both seen and unseen classes.

GENERALIZED ZERO-SHOT LEARNING METRIC LEARNING

Generalized Zero-Shot Recognition Based on Visually Semantic Embedding

CVPR 2019

To bridge the gap, we propose a novel low-dimensional embedding of visual instances that is "visually semantic."

GENERALIZED ZERO-SHOT LEARNING

Compressing Unknown Images With Product Quantizer for Efficient Zero-Shot Classification

CVPR 2019

Based on this intuition, a Product Quantization Zero-Shot Learning (PQZSL) method is proposed to learn embeddings as well as quantizers to compress visual features into compact codes for Approximate NN (ANN) search.

GENERALIZED ZERO-SHOT LEARNING QUANTIZATION

Hierarchical Disentanglement of Discriminative Latent Features for Zero-Shot Learning

CVPR 2019

Most studies in zero-shot learning model the relationship, in the form of a classifier or mapping, between features from images of seen classes and their attributes.

GENERALIZED ZERO-SHOT LEARNING