FaVCI2D accounts for the wide diversity of facial characteristics of people from across the world by including persons from different regions of the world. The dataset is gender-balanced. Imposter pairs are challenging because they include visually similar faces selected from a large pool of demographically diversified identities. The dataset also includes metadata related to gender, country and age to facilitate fine-grained analysis of results. FaVCI2D is generated from freely distributable resources.