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Expression Classification using Concatenation of Deep Neural Network for the 3rd ABAW3 Competition. (arXiv:2203.12899v2 [cs.CV] UPDATED)
cs.CV updates on arXiv.org arxiv.org
For computers to recognize human emotions, expression classification is an
equally important problem in the human-computer interaction area. In the 3rd
Affective Behavior Analysis In-The-Wild competition, the task of expression
classification includes eight classes with six basic expressions of human faces
from videos. In this paper, we employ a transformer mechanism to encode the
robust representation from the backbone. Fusion of the robust representations
plays an important role in the expression classification task. Our approach
achieves 30.35\% and 28.60\% for …
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