Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Inductive Guided Filter: Real-time Deep Image Matting with Weakly
  Annotated Masks on Mobile Devices   Recently, significant progress has been achieved in deep image matting. Most
of the classical image matting methods are time-consuming and require an ideal
trimap which is difficult to attain in practice. A high efficient image matting
method based on a weakly annotated mask is in demand for mobile applications.
In this paper, we propose a novel method based on Deep Learning and Guided
Filter, called Inductive Guided Filter, which can tackle the real-time general
image matting task on mobile devices. We design a lightweight hourglass network
to parameterize the original Guided Filter method that takes an image and a
weakly annotated mask as input. Further, the use of Gabor loss is proposed for
training networks for complicated textures in image matting. Moreover, we
create an image matting dataset MAT-2793 with a variety of foreground objects.
Experimental results demonstrate that our proposed method massively reduces
running time with robust accuracy.

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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: supr-con
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The categories of this paper are: patt-sol
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The categories of this paper are: eess
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The categories of this paper are: gr-qc
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The categories of this paper are: chao-dyn
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The categories of this paper are: econ
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The categories of this paper are: chem-ph
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The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: math
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The categories of this paper are: ao-sci
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The categories of this paper are: q-alg
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The categories of this paper are: hep-lat
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The categories of this paper are: adap-org