Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SimUSR: A Simple but Strong Baseline for Unsupervised Image
  Super-resolution   In this paper, we tackle a fully unsupervised super-resolution problem, i.e.,
neither paired images nor ground truth HR images. We assume that low resolution
(LR) images are relatively easy to collect compared to high resolution (HR)
images. By allowing multiple LR images, we build a set of pseudo pairs by
denoising and downsampling LR images and cast the original unsupervised problem
into a supervised learning problem but in one level lower. Though this line of
study is easy to think of and thus should have been investigated prior to any
complicated unsupervised methods, surprisingly, there are currently none. Even
more, we show that this simple method outperforms the state-of-the-art
unsupervised method with a dramatically shorter latency at runtime, and
significantly reduces the gap to the HR supervised models. We submitted our
method in NTIRE 2020 super-resolution challenge and won 1st in PSNR, 2nd in
SSIM, and 13th in LPIPS. This simple method should be used as the baseline to
beat in the future, especially when multiple LR images are allowed during the
training phase. However, even in the zero-shot condition, we argue that this
method can serve as a useful baseline to see the gap between supervised and
unsupervised frameworks.

29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
15
The categories of this paper are: nucl-ex
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin