  Facial action unit recognition is an important task for facial analysis.
Owing to the complex collection environment, facial action unit recognition in
the wild is still challenging. The 3rd competition on affective behavior
analysis in-the-wild (ABAW) has provided large amount of facial images with
facial action unit annotations. In this paper, we introduce a facial action
unit recognition method based on transfer learning. We first use available
facial images with expression labels to train the feature extraction network.
Then we fine-tune the network for facial action unit recognition.
