A Topology Standardized 3D Facial Dataset with Emotion and Action Unit Diversity for East Asians.

Abstract

We present a high-resolution 3D facial dataset focused on East Asian participants, designed to provide consistent topology and expression diversity. The dataset includes 98 individuals (18-30 years) and captures neutral faces, six basic emotions, and nine Facial Action Coding System (FACS)-based Action Units (AUs). Each 3D mesh is acquired under a standardized protocol. Synchronized multi-view RGB images are available only for a subset of participants who provided additional consent. To ensure structural consistency across subjects and expressions, we developed a processing pipeline combining FLAME-based expression fitting with Edge-Constrained Non-rigid Iterative Closest Point (Edge-NICP). The resulting meshes share unified topology and vertex correspondence, enabling direct point-to-point comparisons across conditions. Rich annotations, including facial landmarks, verified AU labels, and vertex-level deformation fields, accompany the dataset. Together, these resources may facilitate research in computer graphics, human-computer interaction, and cross-modal studies that benefit from expression-rich, topology-standardized 3D face data.