Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Photometric Mesh Optimization for Video-Aligned 3D Object Reconstruction   In this paper, we address the problem of 3D object mesh reconstruction from
RGB videos. Our approach combines the best of multi-view geometric and
data-driven methods for 3D reconstruction by optimizing object meshes for
multi-view photometric consistency while constraining mesh deformations with a
shape prior. We pose this as a piecewise image alignment problem for each mesh
face projection. Our approach allows us to update shape parameters from the
photometric error without any depth or mask information. Moreover, we show how
to avoid a degeneracy of zero photometric gradients via rasterizing from a
virtual viewpoint. We demonstrate 3D object mesh reconstruction results from
both synthetic and real-world videos with our photometric mesh optimization,
which is unachievable with either na\"ive mesh generation networks or
traditional pipelines of surface reconstruction without heavy manual
post-processing.

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The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: econ
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The categories of this paper are: cond-mat
0
The categories of this paper are: hep-ph
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The categories of this paper are: physics
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The categories of this paper are: bayes-an
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: hep-ex