論文閱讀Synthetic to Real Adaptation with Generative Correlation Alignment Networks
論文題目：Synthetic to Real Adaptation with Generative Correlation Alignment Networks 作者：Xingchao Peng，Kate Saenko 來源： arxiv2017 1. 摘要 文章的想法是如果使用3D CAD建模的合成圖片進行訓練數據的數據增強，將會是一件非常有意義的事。然而，合成圖片與真實圖片之間存在較大的dom
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- 1. Synthetic to real adaptation with generative correlation alignment network
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- 3. 【論文閱讀】Universal Domain Adaptation
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