Generalized Zero-Shot Learning - Unseen

2 papers with code • 0 benchmarks • 0 datasets

The average of the normalized top-1 prediction scores of unseen classes in the generalized zero-shot learning setting, where the label of a test sample is predicted among all (seen + unseen) classes.


Greatest papers with code

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

edgarschnfld/CADA-VAE-PyTorch CVPR 2019

Many approaches in generalized zero-shot learning rely on cross-modal mapping between the image feature space and the class embedding space.

Few-Shot Learning Generalized Few-Shot Learning +3

Gradient Matching Generative Networks for Zero-Shot Learning

mbsariyildiz/gmn-zsl CVPR 2019

In contrast, we propose a generative model that can naturally learn from unsupervised examples, and synthesize training examples for unseen classes purely based on their class embeddings, and therefore, reduce the zero-shot learning problem into a supervised classification task.

Domain Adaptation General Classification +2