  Facial Action Coding System is an important approach of facial expression
analysis.This paper describes our submission to the third Affective Behavior
Analysis (ABAW) 2022 competition. We proposed a transfomer based model to
detect facial action unit (FAU) in video. To be specific, we firstly trained a
multi-modal model to extract both audio and visual feature. After that, we
proposed a action units correlation module to learn relationships between each
action unit labels and refine action unit detection result. Experimental
results on validation dataset shows that our method achieves better performance
than baseline model, which verifies that the effectiveness of proposed network.
