Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computational Emotion Analysis From Images: Recent Advances and Future
  Directions   Emotions are usually evoked in humans by images. Recently, extensive research
efforts have been dedicated to understanding the emotions of images. In this
chapter, we aim to introduce image emotion analysis (IEA) from a computational
perspective with the focus on summarizing recent advances and suggesting future
directions. We begin with commonly used emotion representation models from
psychology. We then define the key computational problems that the researchers
have been trying to solve and provide supervised frameworks that are generally
used for different IEA tasks. After the introduction of major challenges in
IEA, we present some representative methods on emotion feature extraction,
supervised classifier learning, and domain adaptation. Furthermore, we
introduce available datasets for evaluation and summarize some main results.
Finally, we discuss some open questions and future directions that researchers
can pursue.

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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph
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The categories of this paper are: q-bio
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The categories of this paper are: stat
29
The categories of this paper are: funct-an
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The categories of this paper are: cond-mat
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The categories of this paper are: adap-org
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The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: math
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-ex