Towards Inclusive Face Recognition Through Synthetic Ethnicity Alteration

arXiv:2405.01273v1 Announce Type: new
Abstract: Numerous studies have shown that existing Face Recognition Systems (FRS), including commercial ones, often exhibit biases toward certain ethnicities due to under-represented data. In this work, we explore ethnicity alteration and skin tone modification using synthetic face image generation methods to increase the diversity of datasets. We conduct a detailed analysis by first constructing a balanced face image dataset representing three ethnicities: Asian, Black, and Indian. We then make use of existing Generative Adversarial Network-based …

abstract arxiv biases commercial cs.ai cs.cv data datasets diversity explore face face recognition image image generation ones recognition studies synthetic systems through type work