Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Attention for Image Registration (AiR): an unsupervised Transformer
  approach   Image registration as an important basis in signal processing task often
encounter the problem of stability and efficiency. Non-learning registration
approaches rely on the optimization of the similarity metrics between the fix
and moving images. Yet, those approaches are usually costly in both time and
space complexity. The problem can be worse when the size of the image is large
or the deformations between the images are severe. Recently, deep learning, or
precisely saying, the convolutional neural network (CNN) based image
registration methods have been widely investigated in the research community
and show promising effectiveness to overcome the weakness of non-learning based
methods. To explore the advanced learning approaches in image registration
problem for solving practical issues, we present in this paper a method of
introducing attention mechanism in deformable image registration problem. The
proposed approach is based on learning the deformation field with a Transformer
framework (AiR) that does not rely on the CNN but can be efficiently trained on
GPGPU devices also. In a more vivid interpretation: we treat the image
registration problem as the same as a language translation task and introducing
a Transformer to tackle the problem. Our method learns an unsupervised
generated deformation map and is tested on two benchmark datasets. The source
code of the AiR will be released at Gitlab.

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The categories of this paper are: eess
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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: dg-ga
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The categories of this paper are: nucl-ex
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
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: solv-int
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The categories of this paper are: cond-mat
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The categories of this paper are: nlin
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The categories of this paper are: q-fin
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The categories of this paper are: funct-an
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The categories of this paper are: astro-ph
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The categories of this paper are: q-bio