MEGC2020

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.

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

B3 Article in conference proceedings

2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)

J. LI, S. -J. Wang, M. H. Yap, J. See, X. Hong and X. Li, "MEGC2020 - The Third Facial Micro-Expression Grand Challenge," 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), Buenos Aires, Argentina, 2020, pp. 777-780, doi: 10.1109/FG47880.2020.00035

https://doi.org/10.1109/FG47880.2020.00035 http://urn.fi/urn:nbn:fi-fe202103298641