3D Face Tracking from 2D Video through Iterative Dense UV to Image Flow

arXiv:2404.09819v1 Announce Type: new
Abstract: When working with 3D facial data, improving fidelity and avoiding the uncanny valley effect is critically dependent on accurate 3D facial performance capture. Because such methods are expensive and due to the widespread availability of 2D videos, recent methods have focused on how to perform monocular 3D face tracking. However, these methods often fall short in capturing precise facial movements due to limitations in their network architecture, training, and evaluation processes. Addressing these challenges, we …

abstract arxiv availability cs.cv data face face tracking fidelity flow image improving iterative performance through tracking type uncanny valley valley video videos