Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic
  Networks   We propose a novel multi-stream architecture and training methodology that
exploits semantic labels for facial image deblurring. The proposed Uncertainty
Guided Multi- Stream Semantic Network (UMSN) processes regions belonging to
each semantic class independently and learns to combine their outputs into the
final deblurred result. Pixel-wise semantic labels are obtained using a
segmentation network. A predicted confidence measure is used during training to
guide the network towards the challenging regions of the human face such as the
eyes and nose. The entire network is trained in an end- to-end fashion.
Comprehensive experiments on three different face datasets demonstrate that the
proposed method achieves significant improvements over the recent
state-of-the-art face deblurring methods. Code is available at:
https://github.com/ rajeevyasarla/UMSN-Face-Deblurring

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The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
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The categories of this paper are: dg-ga
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
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The categories of this paper are: chem-ph
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The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
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The categories of this paper are: mtrl-th
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The categories of this paper are: cmp-lg