Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatic Photo Adjustment Using Deep Neural Networks   Photo retouching enables photographers to invoke dramatic visual impressions
by artistically enhancing their photos through stylistic color and tone
adjustments. However, it is also a time-consuming and challenging task that
requires advanced skills beyond the abilities of casual photographers. Using an
automated algorithm is an appealing alternative to manual work but such an
algorithm faces many hurdles. Many photographic styles rely on subtle
adjustments that depend on the image content and even its semantics. Further,
these adjustments are often spatially varying. Because of these
characteristics, existing automatic algorithms are still limited and cover only
a subset of these challenges. Recently, deep machine learning has shown unique
abilities to address hard problems that resisted machine algorithms for long.
This motivated us to explore the use of deep learning in the context of photo
editing. In this paper, we explain how to formulate the automatic photo
adjustment problem in a way suitable for this approach. We also introduce an
image descriptor that accounts for the local semantics of an image. Our
experiments demonstrate that our deep learning formulation applied using these
descriptors successfully capture sophisticated photographic styles. In
particular and unlike previous techniques, it can model local adjustments that
depend on the image semantics. We show on several examples that this yields
results that are qualitatively and quantitatively better than previous work.

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The categories of this paper are: gr-qc
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The categories of this paper are: patt-sol
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
12
The categories of this paper are: nucl-th
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The categories of this paper are: nlin
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The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics