Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast and Accurate Single Image Super-Resolution via Information
  Distillation Network   Recently, deep convolutional neural networks (CNNs) have been demonstrated
remarkable progress on single image super-resolution. However, as the depth and
width of the networks increase, CNN-based super-resolution methods have been
faced with the challenges of computational complexity and memory consumption in
practice. In order to solve the above questions, we propose a deep but compact
convolutional network to directly reconstruct the high resolution image from
the original low resolution image. In general, the proposed model consists of
three parts, which are feature extraction block, stacked information
distillation blocks and reconstruction block respectively. By combining an
enhancement unit with a compression unit into a distillation block, the local
long and short-path features can be effectively extracted. Specifically, the
proposed enhancement unit mixes together two different types of features and
the compression unit distills more useful information for the sequential
blocks. In addition, the proposed network has the advantage of fast execution
due to the comparatively few numbers of filters per layer and the use of group
convolution. Experimental results demonstrate that the proposed method is
superior to the state-of-the-art methods, especially in terms of time
performance.

16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th
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The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph