3D Face Modeling via Weakly-supervised Disentanglement Network joint Identity-consistency Prior

arXiv:2404.16536v1 Announce Type: new
Abstract: Generative 3D face models featuring disentangled controlling factors hold immense potential for diverse applications in computer vision and computer graphics. However, previous 3D face modeling methods face a challenge as they demand specific labels to effectively disentangle these factors. This becomes particularly problematic when integrating multiple 3D face datasets to improve the generalization of the model. Addressing this issue, this paper introduces a Weakly-Supervised Disentanglement Framework, denoted as WSDF, to facilitate the training of controllable …

arxiv cs.cv face identity modeling network prior type via weakly-supervised