Augmented Feature Representation with Parallel Convolution for Cross-domain Facial Expression Recognition

Fan Yang, Weicheng Xie, Tao Zhong, Jingyu Hu, Linlin Shen

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

1 Citation (Scopus)


Facial expression recognition (FER) has made significant progress in the past decade, but the inconsistency of distribution between different datasets greatly limits the generalization performance of a learned model on unseen datasets. Recent works resort to aligning feature distributions between domains to improve the cross-domain recognition performance. However, current algorithms use one output each layer for the feature representation, which can not well represent the complex correlation among multi-scale features. To this end, this work proposes a parallel convolution to augment the representation ability of each layer, and introduces an orthogonal regularization to make each convolution represent independent semantic. With the assistance of a self-attention mechanism, the proposed algorithm can generate multiple combinations of multi-scale features to allow the network to better capture the correlation among the outputs of different layers. The proposed algorithm achieves state-of-the-art (SOTA) performances in terms of the average generalization performance on the task of cross-database (CD)-FER. Meanwhile, when AFED or RAF-DB is used for the training, and other four databases, i.e. JAFFE, SFEW, FER2013 and EXPW are used for testing, the proposed algorithm outperforms the baselines by the margins of 5.93% and 2.24% in terms of the average accuracy.

Original languageEnglish
Title of host publicationBiometric Recognition - 16th Chinese Conference, CCBR 2022, Proceedings
EditorsWeihong Deng, Jianjiang Feng, Fang Zheng, Di Huang, Meina Kan, Zhenan Sun, Zhaofeng He, Wenfeng Wang
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783031202322
Publication statusPublished - 2022
Externally publishedYes
Event16th Chinese Conference on Biometric Recognition, CCBR 2022 - Beijing, China
Duration: 11 Nov 202213 Nov 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13628 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th Chinese Conference on Biometric Recognition, CCBR 2022


  • Domain generalization
  • Facial expression recognition
  • Parallel convolution
  • Self-attention

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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