A Self-Fusion Network Based on Contrastive Learning for Group Emotion Recognition

Author:

Wang Xingzhi1,Zhang Dong1ORCID,Tan Hong-Zhou1ORCID,Lee Dah-Jye2ORCID

Affiliation:

1. School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China

2. Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, USA

Funder

National Natural Science Foundation of China

Guangzhou Municipal People–s Livelihood Science and Technology Plan

Science and Technology Program of Guangzhou, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Reference61 articles.

1. Group emotion recognition in the wild by combining deep neural networks for facial expression classification and scene-context analysis

2. Non-volume preserving-based fusion to group-level emotion recognition on crowd videos;quach;arXiv 1811 11849,2018

3. Emotion recognition in the wild using deep neural networks and Bayesian classifiers

4. Using TF-IDF to determine word relevance in document queries;ramos;Proc 1st Instructional Conf Mach Learn,2003

5. Hierarchical Group-level Emotion Recognition in the Wild

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