“Deep Correlations for Texture Synthesis” by Cohen-Or and Sendik
Conference:
Type:
Title:
- Deep Correlations for Texture Synthesis
Session/Category Title: Image Texture & Completion
Presenter(s)/Author(s):
Moderator(s):
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.
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