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CR-Net: A Deep Classification-Regression Network for Multimodal Apparent Personality Analysis

文献类型：期刊论文

作者Li, Yunan5,6; Wan, Jun7,8; Miao, Qiguang5,6; Escalera, Sergio1,2; Fang, Huijuan5,6; Chen, Huizhou5,6; Qi, Xiangda5,6; Guo, Guodong3,4
刊名INTERNATIONAL JOURNAL OF COMPUTER VISION
出版日期2020-03-17
页码18
关键词Personality traits Multimodal data Convolutional neural networks Classification-regression network Bell Loss function
ISSN号0920-5691
DOI10.1007/s11263-020-01309-y
通讯作者Wan, Jun(jun.wan@ia.ac.cn)
英文摘要First impressions strongly influence social interactions, having a high impact in the personal and professional life. In this paper, we present a deep Classification-Regression Network (CR-Net) for analyzing the Big Five personality problem and further assisting on job interview recommendation in a first impressions setup. The setup is based on the ChaLearn First Impressions dataset, including multimodal data with video, audio, and text converted from the corresponding audio data, where each person is talking in front of a camera. In order to give a comprehensive prediction, we analyze the videos from both the entire scene (including the person's motions and background) and the face of the person. Our CR-Net first performs personality trait classification and applies a regression later, which can obtain accurate predictions for both personality traits and interview recommendation. Furthermore, we present a new loss function called Bell Loss to address inaccurate predictions caused by the regression-to-the-mean problem. Extensive experiments on the First Impressions dataset show the effectiveness of our proposed network, outperforming the state-of-the-art.
WOS关键词BIMODAL REGRESSION
资助项目National Key R&D Program of China[2018YFC0807500] ; National Natural Science Foundations of China[61961160704] ; National Natural Science Foundations of China[61876179] ; National Natural Science Foundations of China[61772396] ; National Natural Science Foundations of China[61772392] ; National Natural Science Foundations of China[61902296] ; Fundamental Research Funds for the Central Universities[JBF180301] ; Xi'an Key Laboratory of Big Data and Intelligent Vision[201805053ZD4CG37] ; Science and Technology Development Fund of Macau[0008/2018/A1] ; Science and Technology Development Fund of Macau[0025/2019/A1] ; Science and Technology Development Fund of Macau[0010/2019/AFJ] ; Science and Technology Development Fund of Macau[0025/2019/AKP] ; MINECO/FEDER, UE[TIN2016-74946-P] ; CERCA Programme/Generalitat de Catalunya
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000520662000002
出版者SPRINGER
资助机构National Key R&D Program of China ; National Natural Science Foundations of China ; Fundamental Research Funds for the Central Universities ; Xi'an Key Laboratory of Big Data and Intelligent Vision ; Science and Technology Development Fund of Macau ; MINECO/FEDER, UE ; CERCA Programme/Generalitat de Catalunya
源URL[http://ir.ia.ac.cn/handle/173211/38746]  
专题自动化研究所_模式识别国家重点实验室_生物识别与安全技术研究中心
通讯作者Wan, Jun
作者单位1.Univ Barcelona, Barcelona, Spain
2.Comp Vis Ctr, Barcelona, Spain
3.Natl Engn Lab Deep Learning Technol & Applicat, Beijing, Peoples R China
4.Baidu Res, Inst Deep Learning, Beijing, Peoples R China
5.Xidian Univ, Sch Comp Sci & Technol, Xian, Peoples R China
6.Xian Key Lab Big Data & Intelligent Vis, Xian, Peoples R China
7.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
8.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Li, Yunan,Wan, Jun,Miao, Qiguang,et al. CR-Net: A Deep Classification-Regression Network for Multimodal Apparent Personality Analysis[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2020:18.
APA Li, Yunan.,Wan, Jun.,Miao, Qiguang.,Escalera, Sergio.,Fang, Huijuan.,...&Guo, Guodong.(2020).CR-Net: A Deep Classification-Regression Network for Multimodal Apparent Personality Analysis.INTERNATIONAL JOURNAL OF COMPUTER VISION,18.
MLA Li, Yunan,et al."CR-Net: A Deep Classification-Regression Network for Multimodal Apparent Personality Analysis".INTERNATIONAL JOURNAL OF COMPUTER VISION (2020):18.

入库方式： OAI收割

来源：自动化研究所

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