Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Affect Expression Behaviour Analysis in the Wild using Spatio-Channel
  Attention and Complementary Context Information   Facial expression recognition(FER) in the wild is crucial for building
reliable human-computer interactive systems. However, current FER systems fail
to perform well under various natural and un-controlled conditions. This report
presents attention based framework used in our submission to expression
recognition track of the Affective Behaviour Analysis in-the-wild (ABAW) 2020
competition. Spatial-channel attention net(SCAN) is used to extract local and
global attentive features without seeking any information from landmark
detectors. SCAN is complemented by a complementary context information(CCI)
branch which uses efficient channel attention(ECA) to enhance the relevance of
features. The performance of the model is validated on challenging Aff-Wild2
dataset for categorical expression classification.

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The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
32
The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
8
The categories of this paper are: hep-ex
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The categories of this paper are: quant-ph
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
18
The categories of this paper are: econ
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The categories of this paper are: alg-geom