SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse Attributes

arXiv:2404.17255v1 Announce Type: new
Abstract: AI systems rely on extensive training on large datasets to address various tasks. However, image-based systems, particularly those used for demographic attribute prediction, face significant challenges. Many current face image datasets primarily focus on demographic factors such as age, gender, and skin tone, overlooking other crucial facial attributes like hairstyle and accessories. This narrow focus limits the diversity of the data and consequently the robustness of AI systems trained on them. This work aims to …

abstract age ai systems arxiv building challenges cs.cv current dataset datasets diverse face focus gender however image image datasets large datasets prediction synthetic systems tasks training type