Combating label ambiguity with smooth learning for facial expression recognition

Yifan Chen, Zide Liu, Xuna Wang, Shengnan Xue, Jiahui Yu, Zhaojie Ju

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


Accurately learning facial expression recognition (FER) features using convolutional neural networks (CNNs) is a non-trivial task because of the presence of significant intra-class variability and inter-class similarity as well as the ambiguity of the expressions themselves. Deep metric learning (DML) methods, such as joint central loss and softmax loss optimization, have been adopted by many FER methods to improve the discriminative power of expression recognition models. However, equal supervision of all features with DML methods may include irrelevant features, which ultimately reduces the generalization ability of the learning algorithm. We propose the Attentive Cascaded Network (ACD) method to enhance the discriminative power by adaptively selecting a subset of important feature elements. The proposed ACD integrates multiple feature extractors with smooth center loss to extract to discriminative features. The estimated weights adapt to the sparse representation of central loss to selectively achieve intra-class compactness and inter-class separation of relevant information in the embedding space. The proposed ACD approach is superior compared to state-of-the-art methods.
Original languageEnglish
Title of host publicationIntelligent Robotics and Applications 16th International Conference, ICIRA 2023, Hangzhou, China, July 5–7, 2023, Proceedings, Part II
EditorsHuayong Yang, Honghai Liu, Jun Zou, Zhouping Yin, Lianqing Liu, Geng Yang, Xiaoping Ouyang, Zhiyong Wang
Number of pages10
ISBN (Electronic)9789819964864
ISBN (Print)9789819964857
Publication statusPublished - 10 Oct 2023
EventInternational Conference on Intelligent Robotics and Applications - Hangzhou, China
Duration: 5 Jul 20237 Jul 2023

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence
ISSN (Print)2945-9133
ISSN (Electronic)2945-9141


ConferenceInternational Conference on Intelligent Robotics and Applications


  • deep metric learning
  • ambiguous expressions
  • facial expression recognition

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