MEGC2023: ACM Multimedia 2023 ME Grand Challenge

Adrian K. Davison*, Jingting Li*, Moi Hoon Yap, John See, Wen Huang Cheng, Xiaobai Li, Xiaopeng Hong, Su Jing Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
22 Downloads (Pure)


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 weak and transient nature of MEs, it is difficult for models to distinguish it from other types of facial actions. Therefore, ME in long videos is a challenging task, and the current performance cannot meet the practical application requirements. Addressing these issues, this challenge focuses on ME and the macro-expression (MaE) spotting task. This year, in order to evaluate algorithms' performance more fairly, based on CAS(ME)2, SAMM Long Videos, SMIC-E-long, CAS(ME)3 and 4DME, we build an unseen cross-cultural long-video test set. All participating algorithms are required to run on this test set and submit their results on a leaderboard with a baseline result.

Original languageEnglish
Title of host publicationMM '23: Proceedings of the 31st ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery
Number of pages5
ISBN (Electronic)9798400701085
Publication statusPublished - 27 Oct 2023
Event31st ACM International Conference on Multimedia 2023 - Ottawa, Canada
Duration: 29 Oct 20233 Nov 2023


Conference31st ACM International Conference on Multimedia 2023
Abbreviated titleMM 2023


  • long videos
  • micro-expression
  • spotting

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software


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