@inproceedings{2cd3fc2f145446b3897a72f0d3065779,
title = "Face Tells Detailed Expression: Generating Comprehensive Facial Expression Sentence Through Facial Action Units",
abstract = "Human facial expression plays the key role in the understanding of the social behavior. Many deep learning approaches present facial emotion recognition and automatic image captioning considering human sentiments. However, most current deep learning models for facial expression analysis do not contain comprehensive, detailed information of a single face. In this paper, we newly introduce a text-based facial expression description using several essential components describing comprehensive facial expression: gender, facial action units, and corresponding intensities. Then, we propose comprehensive facial expression sentence generating model along with facial expression recognition model for a single facial image to verify the effectiveness of our text-based dataset. Experimental results show that the proposed two models are supporting each other improving their performances: the text-based facial expression description provides comprehensive semantic information to the facial emotion recognition model. Also, the visual information from the emotion recognition model guides the facial expression sentence generation to produce a proper sentence describing comprehensive description. The text-based dataset is available at https://github.com/joannahong/Text-based-dataset-with-comprehensive-facial-expression-sentence.",
keywords = "Deep learning, Explaining expression from a single face image, Facial action unit based, Facial expression sentence generation",
author = "Joanna Hong and Lee, \{Hong Joo\} and Yelin Kim and Ro, \{Yong Man\}",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 26th International Conference on MultiMedia Modeling, MMM 2020 ; Conference date: 05-01-2020 Through 08-01-2020",
year = "2020",
doi = "10.1007/978-3-030-37734-2\_9",
language = "English",
isbn = "9783030377335",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "100--111",
editor = "Ro, \{Yong Man\} and Junmo Kim and Jung-Woo Choi and Wen-Huang Cheng and Wei-Ta Chu and Peng Cui and Min-Chun Hu and \{De Neve\}, Wesley",
booktitle = "MultiMedia Modeling - 26th International Conference, MMM 2020, Proceedings",
}