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Disentangling Semantic-to-visual Confusion for Zero-shot Learning

By Zihan Ye and others
Using generative models to synthesize visual features from semantic distribution is one of the most popular solutions to ZSL image classification in recent years. The triplet loss (TL) is popularly used to generate realistic visual distributions from semantics by automatically searching discriminative representations. However, the traditional TL cannot search reliable... Show more
June 16, 2021
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Disentangling Semantic-to-visual Confusion for Zero-shot Learning
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