Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Single-Shot Cuboids: Geodesics-based End-to-end Manhattan Aligned Layout
  Estimation from Spherical Panoramas   It has been shown that global scene understanding tasks like layout
estimation can benefit from wider field of views, and specifically spherical
panoramas. While much progress has been made recently, all previous approaches
rely on intermediate representations and postprocessing to produce
Manhattan-aligned estimates. In this work we show how to estimate full room
layouts in a single-shot, eliminating the need for postprocessing. Our work is
the first to directly infer Manhattan-aligned outputs. To achieve this, our
data-driven model exploits direct coordinate regression and is supervised
end-to-end. As a result, we can explicitly add quasi-Manhattan constraints,
which set the necessary conditions for a homography-based Manhattan alignment
module. Finally, we introduce the geodesic heatmaps and loss and a
boundary-aware center of mass calculation that facilitate higher quality
keypoint estimation in the spherical domain. Our models and code are publicly
available at https://vcl3d.github.io/SingleShotCuboids/.

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The categories of this paper are: plasm-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: adap-org
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The categories of this paper are: acc-phys
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The categories of this paper are: mtrl-th
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The categories of this paper are: funct-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: math
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The categories of this paper are: cmp-lg
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The categories of this paper are: cond-mat