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The paper explores the topic of Facial Action Unit (FAU) detection in thewild. 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 FacialExpression Recognition (FER) for the task of FAU detection? The proposednetwork (ResiDen) exploits dense blocks along with residual connections anduses auxiliary information from a FER network. The experiments are performed onthe EmotionNet and DISFA datasets. The experiments show the usefulness offacial expression information for AU detection. The proposed network achievesstate-of-art results on the two databases. Analysis of the results for crossdatabase protocol shows the effectiveness of the network.

Expression Empowered ResiDen Network for Facial Action Unit Detection