Adversarial Feature Distillation for Facial Expression Recognition

Mengchao Bai, Xi Jia, Weicheng Xie, Linlin Shen

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


Human face image contains abundant information including expression, age and gender, etc. Therefore, extracting discriminative feature for certain attribute while expelling others is critical for single facial attribute analysis. In this paper, we propose an adversarial facial expression recognition system, named expression distilling and dispelling learning (ED (formula presented)L), to extract discriminative expression feature from a given face image. The proposed ED (formula presented)L framework composed of two branches, i.e. expression distilling branch ED (formula presented)L-t and expression dispelling branch ED (formula presented)L-p. The ED (formula presented)L-t branch aims to extract the expression-related feature, while the ED (formula presented)L-p branch extracts the non-related feature. The disentangled features jointly serve as a complete representation of the face. Extensive experiments on several benchmark databases, i.e. the CK+, MMI, BU-3DFE and Oulu-CASIA, demonstrate the effectiveness of the proposed ED (formula presented)L framework.

Original languageEnglish
Title of host publicationPRICAI 2019
Subtitle of host publicationTrends in Artificial Intelligence - 16th Pacific Rim International Conference on Artificial Intelligence, Proceedings
EditorsAbhaya C. Nayak, Alok Sharma
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783030298937
Publication statusPublished - 2019
Externally publishedYes
Event16th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2019 - Yanuka Island, Fiji
Duration: 26 Aug 201930 Aug 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11672 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2019
CityYanuka Island


  • Adversarial learning
  • Facial expression recognition
  • Feature dispelling
  • Feature distilling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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