Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics

Yucer, Seyma; Abarghouei, Amir Atapour; Al Moubayed, Noura; Breckon, Toby P.

Abstract

Achieving an effective fine-grained appearance variation over 2D facial images, whilst preserving facial identity, is a challenging task due to the high complexity and entanglement of common 2D facial feature encoding spaces. Despite these challenges, such fine-grained control, by way of disentanglement is a crucial enabler for data-driven racial bias mitigation strategies across multiple automated facial analysis tasks, as it allows to analyse, characterise and synthesise human facial diversity. In this paper, we propose a novel GAN framework to enable fine-grained control over individual race-related phenotype attributes of the facial images. Our framework factors the latent (feature) space into elements that correspond to race-related facial phenotype representations, thereby separating phenotype aspects (e.g. skin, hair colour, nose, eye, mouth shapes), which are notoriously difficult to annotate robustly in real-world facial data. Concurrently, we also introduce a high quality augmented, diverse 2D face image dataset drawn from CelebA-HQ for GAN training. Unlike prior work, our framework only relies upon 2D imagery and related parameters to achieve state-of-the-art individual control over race-related phenotype attributes with improved photo-realistic output.

Citation

Yucer, S., Abarghouei, A. A., Al Moubayed, N., & Breckon, T. P. (2024, June). Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics. Presented at 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 International Joint Conference on Neural Networks (IJCNN)
• Start Date: Jun 30, 2024
• End Date: Jul 5, 2024
• Acceptance Date: Mar 29, 2024
• Online Publication Date: Sep 9, 2024
• Publication Date: Jun 30, 2024
• Deposit Date: Nov 8, 2024
• Publicly Available Date: Dec 12, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 1-10
• Series ISSN: 2161-4393
• Book Title: 2024 International Joint Conference on Neural Networks (IJCNN)
• DOI: https://doi.org/10.1109/ijcnn60899.2024.10650732
• Public URL: https://durham-repository.worktribe.com/output/3086069
• Related Public URLs: https://doi.org/10.48550/arXiv.2403.19897