Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Supervised Adversarial Networks for Image Saliency Detection   In the past few years, Generative Adversarial Network (GAN) became a
prevalent research topic. By defining two convolutional neural networks
(G-Network and D-Network) and introducing an adversarial procedure between them
during the training process, GAN has ability to generate good quality images
that look like natural images from a random vector. Besides image generation,
GAN may have potential to deal with wide range of real world problems. In this
paper, we follow the basic idea of GAN and propose a novel model for image
saliency detection, which is called Supervised Adversarial Networks (SAN).
Specifically, SAN also trains two models simultaneously: the G-Network takes
natural images as inputs and generates corresponding saliency maps (synthetic
saliency maps), and the D-Network is trained to determine whether one sample is
a synthetic saliency map or ground-truth saliency map. However, different from
GAN, the proposed method uses fully supervised learning to learn both G-Network
and D-Network by applying class labels of the training set. Moreover, a novel
kind of layer call conv-comparison layer is introduced into the D-Network to
further improve the saliency performance by forcing the high-level feature of
synthetic saliency maps and ground-truthes as similar as possible. Experimental
results on Pascal VOC 2012 database show that the SAN model can generate high
quality saliency maps for many complicate natural images.

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The categories of this paper are: cond-mat
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The categories of this paper are: stat
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: math
9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-lat
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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: astro-ph
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The categories of this paper are: eess
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The categories of this paper are: hep-ph
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The categories of this paper are: physics
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The categories of this paper are: ao-sci