Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Enhancing Multi-Scale Implicit Learning in Image Super-Resolution with
  Integrated Positional Encoding   Is the center position fully capable of representing a pixel? There is
nothing wrong to represent pixels with their centers in a discrete image
representation, but it makes more sense to consider each pixel as the
aggregation of signals from a local area in an image super-resolution (SR)
context. Despite the great capability of coordinate-based implicit
representation in the field of arbitrary-scale image SR, this area's nature of
pixels is not fully considered. To this end, we propose integrated positional
encoding (IPE), extending traditional positional encoding by aggregating
frequency information over the pixel area. We apply IPE to the state-of-the-art
arbitrary-scale image super-resolution method: local implicit image function
(LIIF), presenting IPE-LIIF. We show the effectiveness of IPE-LIIF by
quantitative and qualitative evaluations, and further demonstrate the
generalization ability of IPE to larger image scales and multiple
implicit-based methods. Code will be released.

9
The categories of this paper are: nlin
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
20
The categories of this paper are: acc-phys
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The categories of this paper are: hep-lat
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
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The categories of this paper are: hep-th
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The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: supr-con
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The categories of this paper are: q-bio