Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep
  Neural Networks   Cloth simulation requires a fast and stable method for interactively and
realistically visualizing fabric materials using computer graphics. We propose
an efficient cloth simulation method using miniature cloth simulation and
upscaling Deep Neural Networks (DNN). The upscaling DNNs generate the target
cloth simulation from the results of physically-based simulations of a
miniature cloth that has similar physical properties to those of the target
cloth. We have verified the utility of the proposed method through experiments,
and the results demonstrate that it is possible to generate fast and stable
cloth simulations under various conditions.

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The categories of this paper are: math
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
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The categories of this paper are: physics
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th