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Found 2 papers, 1 papers with code
Distinguishing Unseen From Seen for Generalized Zero-Shot Learning
In this paper, we present a novel method which leverages both visual and semantic modalities to distinguish seen and unseen categories.
Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
Previous bi-classifier adversarial learning methods only focus on the similarity between the outputs of two distinct classifiers.
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