Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Improved Style Transfer by Respecting Inter-layer Correlations   A popular series of style transfer methods apply a style to a content image
by controlling mean and covariance of values in early layers of a feature
stack. This is insufficient for transferring styles that have strong structure
across spatial scales like, e.g., textures where dots lie on long curves. This
paper demonstrates that controlling inter-layer correlations yields visible
improvements in style transfer methods. We achieve this control by computing
cross-layer, rather than within-layer, gram matrices. We find that (a)
cross-layer gram matrices are sufficient to control within-layer statistics.
Inter-layer correlations improves style transfer and texture synthesis. The
paper shows numerous examples on "hard" real style transfer problems (e.g. long
scale and hierarchical patterns); (b) a fast approximate style transfer method
can control cross-layer gram matrices; (c) we demonstrate that multiplicative,
rather than additive style and content loss, results in very good style
transfer. Multiplicative loss produces a visible emphasis on boundaries, and
means that one hyper-parameter can be eliminated.

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The categories of this paper are: nucl-th
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The categories of this paper are: supr-con
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
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The categories of this paper are: hep-ex
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The categories of this paper are: acc-phys
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The categories of this paper are: funct-an
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The categories of this paper are: adap-org
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The categories of this paper are: chao-dyn
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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: physics
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The categories of this paper are: gr-qc
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The categories of this paper are: econ