Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: 2D Image Relighting with Image-to-Image Translation   With the advent of Generative Adversarial Networks (GANs), a finer level of
control in manipulating various features of an image has become possible. One
example of such fine manipulation is changing the position of the light source
in a scene. This is fundamentally an ill-posed problem, since it requires
understanding the scene geometry to generate proper lighting effects. This
problem is not a trivial one and can become even more complicated if we want to
change the direction of the light source from any direction to a specific one.
Here we provide our attempt to solve this problem using GANs. Specifically,
pix2pix [arXiv:1611.07004] trained with the dataset VIDIT [arXiv:2005.05460]
which contains images of the same scene with different types of light
temperature and 8 different light source positions (N, NE, E, SE, S, SW, W,
NW). The results are 8 neural networks trained to be able to change the
direction of the light source from any direction to one of the 8 previously
mentioned. Additionally, we provide, as a tool, a simple CNN trained to
identify the direction of the light source in an image.

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The categories of this paper are: solv-int
2
The categories of this paper are: math
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
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The categories of this paper are: chem-ph
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
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The categories of this paper are: eess
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The categories of this paper are: atom-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-lat