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For computers to recognize human emotions, expression classification is anequally important problem in the human-computer interaction area. In the 3rdAffective Behavior Analysis In-The-Wild competition, the task of expressionclassification includes eight classes with six basic expressions of human facesfrom videos. In this paper, we employ a transformer mechanism to encode therobust representation from the backbone. Fusion of the robust representationsplays an important role in the expression classification task. Our approachachieves 30.35\% and 28.60\% for the $F_1$ score on the validation set and thetest set, respectively. This result shows the effectiveness of the proposedarchitecture based on the Aff-Wild2 dataset.

Facial Expression Classification using Fusion of Deep Neural Network in Video for the 3rd ABAW3 Competition