Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GRDN:Grouped Residual Dense Network for Real Image Denoising and
  GAN-based Real-world Noise Modeling   Recent research on image denoising has progressed with the development of
deep learning architectures, especially convolutional neural networks. However,
real-world image denoising is still very challenging because it is not possible
to obtain ideal pairs of ground-truth images and real-world noisy images. Owing
to the recent release of benchmark datasets, the interest of the image
denoising community is now moving toward the real-world denoising problem. In
this paper, we propose a grouped residual dense network (GRDN), which is an
extended and generalized architecture of the state-of-the-art residual dense
network (RDN). The core part of RDN is defined as grouped residual dense block
(GRDB) and used as a building module of GRDN. We experimentally show that the
image denoising performance can be significantly improved by cascading GRDBs.
In addition to the network architecture design, we also develop a new
generative adversarial network-based real-world noise modeling method. We
demonstrate the superiority of the proposed methods by achieving the highest
score in terms of both the peak signal-to-noise ratio and the structural
similarity in the NTIRE2019 Real Image Denoising Challenge - Track 2:sRGB.

15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph