Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pixel-Level Domain Transfer   We present an image-conditional image generation model. The model transfers
an input domain to a target domain in semantic level, and generates the target
image in pixel level. To generate realistic target images, we employ the
real/fake-discriminator as in Generative Adversarial Nets, but also introduce a
novel domain-discriminator to make the generated image relevant to the input
image. We verify our model through a challenging task of generating a piece of
clothing from an input image of a dressed person. We present a high quality
clothing dataset containing the two domains, and succeed in demonstrating
decent results.

16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
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The categories of this paper are: adap-org
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol