Deep Impression: Audiovisual Deep Residual Networks for Multimodal Apparent Personality Trait Recognition (pdf link)
Yagmur Gucluturk, Umut Guclu, Marcel A. J. van Gerven, Rob van Lier,
Radboud University, Donders Institute for Brain, Cognition
Abstract. Here, we develop an audiovisual deep residual network for
multimodal apparent personality trait recognition. The network is trained
end-to-end for predicting the Big Five personality traits of people from
their videos. That is, the network does not require any feature engineering
or visual analysis such as face detection, face landmark alignment or
facial expression recognition. Recently, the network won the third place
in the ChaLearn First Impressions Challenge with a test accuracy of
0.9109.
Keywords: Big Five personality traits, audiovisual, deep neural network,
deep residual network, multimodal.
Yagmur Gucluturk, Umut Guclu, Marcel A. J. van Gerven, Rob van Lier,
Radboud University, Donders Institute for Brain, Cognition
Quote:
Abstract. Here, we develop an audiovisual deep residual network for
multimodal apparent personality trait recognition. The network is trained
end-to-end for predicting the Big Five personality traits of people from
their videos. That is, the network does not require any feature engineering
or visual analysis such as face detection, face landmark alignment or
facial expression recognition. Recently, the network won the third place
in the ChaLearn First Impressions Challenge with a test accuracy of
0.9109.
Keywords: Big Five personality traits, audiovisual, deep neural network,
deep residual network, multimodal.