Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Detector-oblivious Multi-arm Network for Keypoint Matching   This paper presents a matching network to establish point correspondence
between images. We propose a Multi-Arm Network (MAN) to learn region overlap
and depth, which can greatly improve the keypoint matching robustness while
bringing little computational cost during the inference stage. Another design
that makes this framework different from many existing learning based pipelines
that require re-training when a different keypoint detector is adopted, our
network can directly work with different keypoint detectors without such a
time-consuming re-training process. Comprehensive experiments conducted on
outdoor and indoor datasets demonstrated that our proposed MAN outperforms
state-of-the-art methods. Code will be made publicly available.

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The categories of this paper are: eess
31
The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-bio
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The categories of this paper are: cmp-lg
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The categories of this paper are: solv-int
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The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
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The categories of this paper are: nlin
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The categories of this paper are: stat
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The categories of this paper are: alg-geom
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The categories of this paper are: funct-an
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The categories of this paper are: hep-ex
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The categories of this paper are: chem-ph
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The categories of this paper are: acc-phys