Using photorealistic face synthesis and domain adaptation to improve facial expression analysis

Behzad Bozorgtabar, Mohammad Saeed Rad, Hazim Kemal Ekenel, Jean Philippe Thiran

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

Abstract

Cross-domain synthesizing realistic faces to learn deep models has attracted increasing attention for facial expression analysis as it helps to improve the performance of expression recognition accuracy despite having small number of real training images. However, learning from synthetic face images can be problematic due to the distribution discrepancy between low-quality synthetic images and real face images and may not achieve the desired performance when the learned model applies to real world scenarios. To this end, we propose a new attribute guided face image synthesis to perform a translation between multiple image domains using a single model. In addition, we adopt the proposed model to learn from synthetic faces by matching the feature distributions between different domains while preserving each domain's characteristics. We evaluate the effectiveness of the proposed approach on several face datasets on generating realistic face images. We demonstrate that the expression recognition performance can be enhanced by benefiting from our face synthesis model. Moreover, we also conduct experiments on a near-infrared dataset containing facial expression videos of drivers to assess the performance using in-the-wild data for driver emotion recognition.

Original languageEnglish (US)
Title of host publicationProceedings - 14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728100890
DOIs
StatePublished - May 2019
Event14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019 - Lille, France
Duration: May 14 2019May 18 2019

Publication series

NameProceedings - 14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019

Conference

Conference14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019
Country/TerritoryFrance
CityLille
Period5/14/195/18/19

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Media Technology

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