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MEGC2022: ACM Multimedia 2022 Micro-Expression Grand Challenge

Authors:

Wen-Huang Cheng,

Adrian K. Davison,

Zizhao DongAuthors Info & Claims

MM '22: Proceedings of the 30th ACM International Conference on Multimedia

Pages 7170 - 7174

https://doi.org/10.1145/3503161.3551601

Published: 10 October 2022 Publication History

Abstract

Facial micro-expressions (MEs) are involuntary movements of the face that occur spontaneously when a person experiences an emotion but attempts to suppress or repress the facial expression, typically found in a high-stakes environment. Unfortunately, the small sample problem severely limits the automation of ME analysis. Furthermore, due to the brief and subtle nature of ME, ME spotting is a challenging task, and the performance is still not satisfactory yet. This challenge focuses on two tasks, i.e., the micro- and macro-expression spotting task, and the ME Generation task.

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MP4 File (mm22-mmgc54.mp4)

Facial micro-expressions (MEs) are involuntary movements of the face that occur spontaneously when a person experiences an emotion but attempts to suppress or repress the facial expression, typically found in a high-stakes environment. Unfortunately, the small sample problem severely limits the automation of ME analysis. Furthermore, due to the brief and subtle nature of ME, ME spotting is a challenging task, and the performance is still not satisfactory yet. This challenge focuses on two tasks, i.e., the micro- and macro-expression spotting task, and the ME Generation task. Eight teams participated in the spotting task and three teams participated in the generation task, respectively. The top three articles for each task were accepted.

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Cited By

Zhang DZhang TSun HTang YLiu Q(2024)MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial CodingSensors10.3390/s2423754924:23(7549)Online publication date: 26-Nov-2024
https://doi.org/10.3390/s24237549
Zhao STang HMao XLiu SZhang YWang HXu TChen E(2024)DFME: A New Benchmark for Dynamic Facial Micro-Expression RecognitionIEEE Transactions on Affective Computing10.1109/TAFFC.2023.334191815:3(1371-1386)Online publication date: Jul-2024
https://doi.org/10.1109/TAFFC.2023.3341918
Wang LCai THuang PLiu XCai W(2024)Two-Stage Facial Expression Spotting with Spectrum-Based Post-Processing2024 IEEE International Conference on Multimedia and Expo (ICME)10.1109/ICME57554.2024.10687531(1-6)Online publication date: 15-Jul-2024
https://doi.org/10.1109/ICME57554.2024.10687531
Show More Cited By

Index Terms

MEGC2022: ACM Multimedia 2022 Micro-Expression Grand Challenge
1. Applied computing
  1. Law, social and behavioral sciences
    1. Psychology
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

cover image ACM Conferences

MM '22: Proceedings of the 30th ACM International Conference on Multimedia

October 2022

7537 pages

ISBN:9781450392037

DOI:10.1145/3503161

General Chairs:
João Magalhães
NOVA University of Lisbon, Portugal
,
Alberto del Bimbo
University of Florence, Italy
,
Shin'ichi Satoh
National Institute of Informatics, Japan
,
Nicu Sebe
University of Trento, Italy
,
Program Chairs:
Xavier Alameda-Pineda
Inria, Grenoble, France
,
Qin Jin
Renmin University of China, China
,
Vincent Oria
New Jersey Institute of Technology, USA
,
Laura Toni
University College London, UK

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 October 2022

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Academy of Finland
The Manchester Metropolitan University VC PhD Studentship
Ministry of Science and Technology of Taiwan
National Natural Science Foundation of China

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MM '22

Sponsor:

SIGMM

MM '22: The 30th ACM International Conference on Multimedia

October 10 - 14, 2022

Lisboa, Portugal

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

Zhang DZhang TSun HTang YLiu Q(2024)MCCA-VNet: A Vit-Based Deep Learning Approach for Micro-Expression Recognition Based on Facial CodingSensors10.3390/s2423754924:23(7549)Online publication date: 26-Nov-2024
https://doi.org/10.3390/s24237549
Zhao STang HMao XLiu SZhang YWang HXu TChen E(2024)DFME: A New Benchmark for Dynamic Facial Micro-Expression RecognitionIEEE Transactions on Affective Computing10.1109/TAFFC.2023.334191815:3(1371-1386)Online publication date: Jul-2024
https://doi.org/10.1109/TAFFC.2023.3341918
Wang LCai THuang PLiu XCai W(2024)Two-Stage Facial Expression Spotting with Spectrum-Based Post-Processing2024 IEEE International Conference on Multimedia and Expo (ICME)10.1109/ICME57554.2024.10687531(1-6)Online publication date: 15-Jul-2024
https://doi.org/10.1109/ICME57554.2024.10687531
Liong GLiong SChan CSee J(2024)SFAMNetNeurocomputing10.1016/j.neucom.2023.126998566:COnline publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.neucom.2023.126998
He EChen QZhong Q(2023)SL-Swin: A Transformer-Based Deep Learning Approach for Macro- and Micro-Expression Spotting on Small-Size Expression DatasetsElectronics10.3390/electronics1212265612:12(2656)Online publication date: 13-Jun-2023
https://doi.org/10.3390/electronics12122656
Qin WZou BLi XWang WMa HEl Saddik AMei TCucchiara RBertini MTobon Vallejo DAtrey PHossain M(2023)Micro-Expression Spotting with Face Alignment and Optical FlowProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3612853(9501-9505)Online publication date: 26-Oct-2023
https://dl.acm.org/doi/10.1145/3581783.3612853
Dhall ASingh MGoecke RGedeon TZeng DWang YIkeda K(2023)EmotiW 2023: Emotion Recognition in the Wild ChallengeProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3616545(746-749)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3577190.3616545

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