Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Object Tracking by Reconstruction with View-Specific Discriminative
  Correlation Filters   Standard RGB-D trackers treat the target as an inherently 2D structure, which
makes modelling appearance changes related even to simple out-of-plane rotation
highly challenging. We address this limitation by proposing a novel long-term
RGB-D tracker - Object Tracking by Reconstruction (OTR). The tracker performs
online 3D target reconstruction to facilitate robust learning of a set of
view-specific discriminative correlation filters (DCFs). The 3D reconstruction
supports two performance-enhancing features: (i) generation of accurate spatial
support for constrained DCF learning from its 2D projection and (ii) point
cloud based estimation of 3D pose change for selection and storage of
view-specific DCFs which are used to robustly localize the target after
out-of-view rotation or heavy occlusion. Extensive evaluation of OTR on the
challenging Princeton RGB-D tracking and STC Benchmarks shows it outperforms
the state-of-the-art by a large margin.

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The categories of this paper are: eess
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The categories of this paper are: dg-ga
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The categories of this paper are: acc-phys
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The categories of this paper are: econ
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
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The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
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The categories of this paper are: physics
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The categories of this paper are: nucl-th
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The categories of this paper are: funct-an
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The categories of this paper are: adap-org
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The categories of this paper are: stat
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The categories of this paper are: chem-ph