Portrait4D-v2: Pseudo Multi-View Data Creates Better 4D Head Synthesizer

arXiv:2403.13570v1 Announce Type: new
Abstract: In this paper, we propose a novel learning approach for feed-forward one-shot 4D head avatar synthesis. Different from existing methods that often learn from reconstructing monocular videos guided by 3DMM, we employ pseudo multi-view videos to learn a 4D head synthesizer in a data-driven manner, avoiding reliance on inaccurate 3DMM reconstruction that could be detrimental to the synthesis performance. The key idea is to first learn a 3D head synthesizer using synthetic multi-view images to …

abstract arxiv avatar cs.cv data data-driven head learn novel paper synthesis type videos view