Web: http://arxiv.org/abs/2209.05434

Sept. 21, 2022, 1:13 a.m. | Junshu Tang, Bo Zhang, Binxin Yang, Ting Zhang, Dong Chen, Lizhuang Ma, Fang Wen

cs.CV updates on arXiv.org arxiv.org

In contrast to the traditional avatar creation pipeline which is a costly
process, contemporary generative approaches directly learn the data
distribution from photographs. While plenty of works extend unconditional
generative models and achieve some levels of controllability, it is still
challenging to ensure multi-view consistency, especially in large poses. In
this work, we propose a network that generates 3D-aware portraits while being
controllable according to semantic parameters regarding pose, identity,
expression and illumination. Our network uses neural scene representation to …


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