Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Classification Leveraged Object Detector   Currently, the state-of-the-art image classification algorithms outperform
the best available object detector by a big margin in terms of average
precision. We, therefore, propose a simple yet principled approach that allows
us to leverage object detection through image classification on supporting
regions specified by a preliminary object detector. Using a simple bag-of-
words model based image classification algorithm, we leveraged the performance
of the deformable model objector from 35.9% to 39.5% in average precision over
20 categories on standard PASCAL VOC 2007 detection dataset.

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The categories of this paper are: comp-gas
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The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex
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The categories of this paper are: q-alg
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The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat
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The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
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The categories of this paper are: patt-sol
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The categories of this paper are: plasm-ph
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The categories of this paper are: stat
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The categories of this paper are: chao-dyn
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The categories of this paper are: bayes-an
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The categories of this paper are: quant-ph
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The categories of this paper are: math-ph
3
The categories of this paper are: physics