Hu Min)As the one of most powerful and natural signals of expressing emotion states [1], facial emotions account for the 55% role of emotional information [2]. Due to the influence of many factors, such as different subjects, races, illumination, complex background and so on, facial emotion analysis is a indubitable challenging task. Most of the previous researches [3,4,5] were based on data in laboratory-controlled environment which can avoid many factors mentioned above with the limitation of the number of datasets and algorithm. Compared to facial emotion recognition(FER) in laboratory-controlled environment, FER in-the-wild is closer to the business application. Nowadays, several works about FER in-the-wild has gradually
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