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- W4241568739 abstract "Example-based texture synthesis has been an active research problem for over two decades. Still, synthesizing textures with nonlocal structures remains a challenge. In this article, we present a texture synthesis technique that builds upon convolutional neural networks and extracted statistics of pretrained deep features. We introduce a structural energy, based on correlations among deep features, which capture the self-similarities and regularities characterizing the texture. Specifically, we show that our technique can synthesize textures that have structures of various scales, local and nonlocal, and the combination of the two." @default.
- W4241568739 created "2022-05-12" @default.
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- W4241568739 date "2017-07-25" @default.
- W4241568739 modified "2023-10-06" @default.
- W4241568739 title "Deep Correlations for Texture Synthesis" @default.
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- W4241568739 doi "https://doi.org/10.1145/3072959.3015461" @default.
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