MEGC2020 - The Third Facial Micro-Expression Grand Challenge

Jingting Li, Su-Jing Wang*, Moi Hoon Yap, John See, Xiaopeng Hong, Xiaobai Li

*Corresponding author for this work

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

20 Citations (Scopus)

Abstract

The recent emergence of automatic facial micro-expression analysis has attracted a lot of attention in the last five years. Compared to the advances made in micro-expression recognition, the task of micro-expression spotting from long videos is tremendously in need of more effective methods. This paper summarises the 3rd Facial Micro-Expression Grand Challenge (MEGC 2020) held in conjunction with the 15th IEEE Conference on Automatic Face and Gesture Recognition (FG) 2020. In this workshop, we propose a new challenge of spotting both macro-and micro-expressions from long videos, to spur the community to develop new techniques for micro-expression spotting and also to extend facial micro-expression analysis to more complex real-world scenarios where micro-expressions are likely to be intertwined among normal expressions. In this paper, we outline the evaluation protocols for the challenge task, and describe the datasets involved. Then, we summarize the methods from the accepted challenge papers, present the comparison and analysis of results, as well as future directions.

Original languageEnglish
Title of host publication2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
EditorsVitomir Struc, Francisco Gomez-Fernandez
PublisherIEEE
Pages777-780
Number of pages4
ISBN (Electronic)9781728130798
DOIs
Publication statusPublished - 18 Jan 2021
Event15th IEEE International Conference on Automatic Face and Gesture Recognition 2020 - Buenos Aires, Argentina
Duration: 16 Nov 202020 Nov 2020

Conference

Conference15th IEEE International Conference on Automatic Face and Gesture Recognition 2020
Abbreviated titleFG 2020
Country/TerritoryArgentina
CityBuenos Aires
Period16/11/2020/11/20

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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