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MEGC2022: ACM Multimedia 2022 Micro-Expression Grand Challenge

  • Jingting Li
  • , Moi Hoon Yap
  • , Wen Huang Cheng
  • , John See
  • , Xiaopeng Hong
  • , Xiaobai Li
  • , Su Jing Wang*
  • , Adrian K. Davison
  • , Yante Li
  • , Zizhao Dong
  • *Corresponding author for this work
  • CAS - Institute of Psychology
  • Manchester Metropolitan University
  • National Yang Ming Chiao Tung University
  • Heriot-Watt University
  • University of Oulu
  • University of Chinese Academy of Sciences
  • Harbin Institute of Technology
  • University of Manchester

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationMM 2022 - Proceedings of the 30th ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages7170-7174
Number of pages5
ISBN (Electronic)9781450392037
DOIs
StatePublished - 10 Oct 2022
Event30th ACM International Conference on Multimedia, MM 2022 - Lisboa, Portugal
Duration: 10 Oct 202214 Oct 2022

Publication series

NameMM 2022 - Proceedings of the 30th ACM International Conference on Multimedia

Conference

Conference30th ACM International Conference on Multimedia, MM 2022
Country/TerritoryPortugal
CityLisboa
Period10/10/2214/10/22

Keywords

  • generation
  • micro-expression
  • spotting

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