Eye Motion Matters for 3D Face Reconstruction
This work addresses a specific challenge in 3D face reconstruction for applications requiring detailed facial modeling, but it is incremental as it focuses on improving eye region dynamics within an established framework.
The paper tackles the problem of single-image 3D face reconstruction by addressing the neglect of eye dynamics in existing methods, introducing an Eye Landmark Adjustment Module and Local Dynamic Loss to capture eye features, resulting in superior performance on two datasets.
Recent advances in single-image 3D face reconstruction have shown remarkable progress in various applications. Nevertheless, prevailing techniques tend to prioritize the global facial contour and expression, often neglecting the nuanced dynamics of the eye region. In response, we introduce an Eye Landmark Adjustment Module, complemented by a Local Dynamic Loss, designed to capture the dynamic features of the eyes area. Our module allows for flexible adjustment of landmarks, resulting in accurate recreation of various eye states. In this paper, we present a comprehensive evaluation of our approach, conducting extensive experiments on two datasets. The results underscore the superior performance of our approach, highlighting its significant contributions in addressing this particular challenge.