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arXiv · 2107.03143

Action Units Recognition Using Improved Pairwise Deep Architecture

Junya Saito·Xiaoyu Mi·Akiyoshi Uchida·Sachihiro Youoku·Takahisa Yamamoto·Kentaro Murase·Osafumi Nakayama
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Abstract

Facial Action Units (AUs) represent a set of facial muscular activities and various combinations of AUs can represent a wide range of emotions. AU recognition is often used in many applications, including marketing, healthcare, education, and so forth. Although a lot of studies have developed various methods to improve recognition accuracy, it still remains a major challenge for AU recognition. In the Affective Behavior Analysis in-the-wild (ABAW) 2020 competition, we proposed a new automatic Action Units (AUs) recognition method using a pairwise deep architecture to derive the Pseudo-Intensities of each AU and then convert them into predicted intensities. This year, we introduced a new technique to last year's framework to further reduce AU recognition errors due to temporary face occlusion such as hands on face or large face orientation. We obtained a score of 0.65 in the validation data set for this year's competition.

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Junya Saito, Xiaoyu Mi, Akiyoshi Uchida, Sachihiro Youoku, Takahisa Yamamoto, Kentaro Murase, Osafumi Nakayama. 2021-07-07. Action Units Recognition Using Improved Pairwise Deep Architecture. https://arxiv.org/abs/2107.03143

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