2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDIMA-ELI-1.1
Paper Title Identity-Free Facial Expression Recognition using conditional Generative Adversarial Network
Authors Jie Cai, Zibo Meng, InnoPeak Technology, United States; Ahmed Shehab Khan, James O’Reilly, Zhiyuan Li, University of South Carolina, United States; Shizhong Han, Qualcomm AI Research, United States; Yan Tong, University of South Carolina, United States
SessionIMA-ELI-1: Imaging and Media Applications + Electronic Imaging
LocationArea F
Session Time:Monday, 20 September, 15:30 - 17:00
Presentation Time:Monday, 20 September, 15:30 - 17:00
Presentation Poster
Topic Imaging and Media Applications: Image and video processing over networks
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Abstract A novel Identity-Free conditional Generative Adversarial Network (IF-GAN) was proposed for Facial Expression Recognition (FER) to explicitly reduce high inter-subject variations caused by identity-related facial attributes, e.g., age, race, and gender. As part of an end-to-end system, a cGAN was designed to transform a given input facial expression to an “average” identity face with the same expression as the input. Then, identity-free FER is possible since the generated images have the same synthetic “average” identity and differ only in their displayed expressions. Experiments on four facial expression datasets, one with spontaneous expressions, show that IF-GAN outperforms the baseline CNN and achieves state-of-the-art performance for FER.