Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Depth Completion of a Single RGB-D Image   The goal of our work is to complete the depth channel of an RGB-D image.
Commodity-grade depth cameras often fail to sense depth for shiny, bright,
transparent, and distant surfaces. To address this problem, we train a deep
network that takes an RGB image as input and predicts dense surface normals and
occlusion boundaries. Those predictions are then combined with raw depth
observations provided by the RGB-D camera to solve for depths for all pixels,
including those missing in the original observation. This method was chosen
over others (e.g., inpainting depths directly) as the result of extensive
experiments with a new depth completion benchmark dataset, where holes are
filled in training data through the rendering of surface reconstructions
created from multiview RGB-D scans. Experiments with different network inputs,
depth representations, loss functions, optimization methods, inpainting
methods, and deep depth estimation networks show that our proposed approach
provides better depth completions than these alternatives.

4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
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The categories of this paper are: physics
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The categories of this paper are: q-alg
18
The categories of this paper are: econ
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
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The categories of this paper are: chao-dyn
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The categories of this paper are: solv-int