Audio-Visual Group-based Emotion Recognition using Local and Global Feature Aggregation based Multi-Task Learning-Reference-Cited by-同舟云学术

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Audio-Visual Group-based Emotion Recognition using Local and Global Feature Aggregation based Multi-Task Learning

Published:2023-10-09 Issue: Volume: Page:
ISSN:
Container-title:INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION
language:
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Author:

Li Sunan¹^ORCID,Lian Hailun¹^ORCID,Lu Cheng²^ORCID,Zhao Yan¹^ORCID,Tang Chuangao²^ORCID,Zong Yuan²^ORCID,Zheng Wenming³^ORCID

Affiliation:

1. School of Information Science and Engineering, Southeast University, China

2. School of Biological Science and Medical Engineering, Southeast University, China

3. Key Laboratory of Child Development and Learning Science of Ministry of Education, Southeast University, China

Funder

NSFC

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3577190.3616544

Reference17 articles.

1. Alexei Baevski , Yuhao Zhou , Abdelrahman Mohamed , and Michael Auli . 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems 33 ( 2020 ), 12449–12460. Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems 33 (2020), 12449–12460.

2. EmotiW 2020: Driver Gaze, Group Emotion, Student Engagement and Physiological Signal based Challenges

3. EmotiW 2023: Emotion Recognition in the Wild Challenge

4. Challenges in Representation Learning: A Report on Three Machine Learning Contests

5. Deep Residual Learning for Image Recognition

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