Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cross-Scale Internal Graph Neural Network for Image Super-Resolution   Non-local self-similarity in natural images has been well studied as an
effective prior in image restoration. However, for single image
super-resolution (SISR), most existing deep non-local methods (e.g., non-local
neural networks) only exploit similar patches within the same scale of the
low-resolution (LR) input image. Consequently, the restoration is limited to
using the same-scale information while neglecting potential high-resolution
(HR) cues from other scales. In this paper, we explore the cross-scale patch
recurrence property of a natural image, i.e., similar patches tend to recur
many times across different scales. This is achieved using a novel cross-scale
internal graph neural network (IGNN). Specifically, we dynamically construct a
cross-scale graph by searching k-nearest neighboring patches in the downsampled
LR image for each query patch in the LR image. We then obtain the corresponding
k HR neighboring patches in the LR image and aggregate them adaptively in
accordance to the edge label of the constructed graph. In this way, the HR
information can be passed from k HR neighboring patches to the LR query patch
to help it recover more detailed textures. Besides, these internal
image-specific LR/HR exemplars are also significant complements to the external
information learned from the training dataset. Extensive experiments
demonstrate the effectiveness of IGNN against the state-of-the-art SISR methods
including existing non-local networks on standard benchmarks.

10
The categories of this paper are: q-bio
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The categories of this paper are: quant-ph
3
The categories of this paper are: physics
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
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The categories of this paper are: q-alg
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The categories of this paper are: funct-an
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The categories of this paper are: bayes-an
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The categories of this paper are: astro-ph
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The categories of this paper are: eess
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The categories of this paper are: acc-phys