Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Technical Report for Valence-Arousal Estimation in ABAW2 Challenge   In this work, we describe our method for tackling the valence-arousal
estimation challenge from ABAW2 ICCV-2021 Competition. The competition
organizers provide an in-the-wild Aff-Wild2 dataset for participants to analyze
affective behavior in real-life settings. We use a two stream model to learn
emotion features from appearance and action respectively. To solve data
imbalanced problem, we apply label distribution smoothing (LDS) to re-weight
labels. Our proposed method achieves Concordance Correlation Coefficient (CCC)
of 0.591 and 0.617 for valence and arousal on the validation set of Aff-wild2
dataset.

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The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-th
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The categories of this paper are: q-bio
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The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
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The categories of this paper are: plasm-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
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The categories of this paper are: solv-int
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The categories of this paper are: nucl-ex
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The categories of this paper are: gr-qc
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The categories of this paper are: dg-ga
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The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg