Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Local- and Holistic- Structure Preserving Image Super Resolution via
  Deep Joint Component Learning   Recently, machine learning based single image super resolution (SR)
approaches focus on jointly learning representations for high-resolution (HR)
and low-resolution (LR) image patch pairs to improve the quality of the
super-resolved images. However, due to treat all image pixels equally without
considering the salient structures, these approaches usually fail to produce
visual pleasant images with sharp edges and fine details. To address this
issue, in this work we present a new novel SR approach, which replaces the main
building blocks of the classical interpolation pipeline by a flexible,
content-adaptive deep neural networks. In particular, two well-designed
structure-aware components, respectively capturing local- and holistic- image
contents, are naturally incorporated into the fully-convolutional
representation learning to enhance the image sharpness and naturalness.
Extensively evaluations on several standard benchmarks (e.g., Set5, Set14 and
BSD200) demonstrate that our approach can achieve superior results, especially
on the image with salient structures, over many existing state-of-the-art SR
methods under both quantitative and qualitative measures.

23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat