Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation   Transparent objects are a common part of everyday life, yet they possess
unique visual properties that make them incredibly difficult for standard 3D
sensors to produce accurate depth estimates for. In many cases, they often
appear as noisy or distorted approximations of the surfaces that lie behind
them. To address these challenges, we present ClearGrasp -- a deep learning
approach for estimating accurate 3D geometry of transparent objects from a
single RGB-D image for robotic manipulation. Given a single RGB-D image of
transparent objects, ClearGrasp uses deep convolutional networks to infer
surface normals, masks of transparent surfaces, and occlusion boundaries. It
then uses these outputs to refine the initial depth estimates for all
transparent surfaces in the scene. To train and test ClearGrasp, we construct a
large-scale synthetic dataset of over 50,000 RGB-D images, as well as a
real-world test benchmark with 286 RGB-D images of transparent objects and
their ground truth geometries. The experiments demonstrate that ClearGrasp is
substantially better than monocular depth estimation baselines and is capable
of generalizing to real-world images and novel objects. We also demonstrate
that ClearGrasp can be applied out-of-the-box to improve grasping algorithms'
performance on transparent objects. Code, data, and benchmarks will be
released. Supplementary materials available on the project website:
https://sites.google.com/view/cleargrasp

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The categories of this paper are: astro-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: bayes-an
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The categories of this paper are: gr-qc
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The categories of this paper are: q-fin
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The categories of this paper are: atom-ph
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The categories of this paper are: q-alg
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The categories of this paper are: hep-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: physics
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The categories of this paper are: hep-ex
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The categories of this paper are: econ
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The categories of this paper are: nlin
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-ex