Browse State-of-the-Art › Generalized Zero-Shot Learning - Unseen
Generalized Zero-Shot Learning - Unseen
2 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
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.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
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Most implemented papers archive 2025-07-28
2 shown of 2 papers with code (2 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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1 Jun 2019 1 repository listedIn 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…
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1 Jun 2019 1 repository listedMany approaches in generalized zero-shot learning rely on cross-modal mapping between the image feature space and the class embedding space.
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