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Instance-dependent label noise learning via separating style from content
DOI:10.1016/j.patrec.2025.04.039.png)
Abstract
En 中文
• Separates content and style to handle instance-dependent label noise. • Combines generative modeling with semi-supervised learning for noisy labels. • Outperforms state-of-the-art on noisy datasets like CIFAR-0 and Clothing1M.
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3.3
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7.8K
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1.6W
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