Leveraging Balanced Semantic Embedding for Generative Zero-Shot Learning.
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DOI: 10.1109/tnnls.2022.3208525
Abstract: Generative (generalized) zero-shot learning (G)ZSL models aim to synthesize unseen class features by using only seen class feature and attribute pairs as training data. However, the generated fake unseen features tend to be dominated by… read more here.
Keywords: embedding generative; balanced semantic; semantic embedding; shot learning ... See more keywords