  The paper explores the topic of Facial Action Unit (FAU) detection in the
wild. In particular, we are interested in answering the following questions:
(1) how useful are residual connections across dense blocks for face analysis?
(2) how useful is the information from a network trained for categorical Facial
Expression Recognition (FER) for the task of FAU detection? The proposed
network (ResiDen) exploits dense blocks along with residual connections and
uses auxiliary information from a FER network. The experiments are performed on
the EmotionNet and DISFA datasets. The experiments show the usefulness of
facial expression information for AU detection. The proposed network achieves
state-of-art results on the two databases. Analysis of the results for cross
database protocol shows the effectiveness of the network.
