Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GAN Computers Generate Arts? A Survey on Visual Arts, Music, and
  Literary Text Generation using Generative Adversarial Network   "Art is the lie that enables us to realize the truth." - Pablo Picasso. For
centuries, humans have dedicated themselves to producing arts to convey their
imagination. The advancement in technology and deep learning in particular, has
caught the attention of many researchers trying to investigate whether art
generation is possible by computers and algorithms. Using generative
adversarial networks (GANs), applications such as synthesizing photorealistic
human faces and creating captions automatically from images were realized. This
survey takes a comprehensive look at the recent works using GANs for generating
visual arts, music, and literary text. A performance comparison and description
of the various GAN architecture are also presented. Finally, some of the key
challenges in art generation using GANs are highlighted along with
recommendations for future work.

11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
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The categories of this paper are: solv-int
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The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
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The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
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The categories of this paper are: adap-org