RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs

We propose a novel approach for the single-view 3D face reconstruction task in a non-parametric scheme. Our method gets rid of the heavy dependence on the statistic model and, therefore, its limitations and achieves state-of-the-art performance by learning from our created pseudo 2D&3D datasets.
AAAI 2023 Paper (Oral)    Project Page    Code