本文提出了PAniC-3D系统，可直接从动漫角色的插画式人像中重建风格化的三维角色头部。与自然人类头部的照片相比，动漫角色立绘插画中的发型和饰品具有更复杂和多样的几何形状，并带有非真实主义的轮廓线。此外，缺乏适用于训练和评估这种模糊的风格化重建任务的三维模型和肖像插画数据。面对这些挑战，本文提出的PAniC-3D架构采用线条填充模型跨越了从插画到三维域的差距，并使用体积辐射场表示复杂的几何形状。本文使用两个新的大型数据集（11.2k个Vroid 3D模型、1k个Vtuber肖像插画）对系统进行训练，并在新颖的AnimeRecon插画至3D对的基准测试中进行了评估。PAniC-3D显著优于基线方法，并提供了数据来建立从肖像插画中进行风格化重建的任务。
标题：PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters
作者：Shuhong Chen, Kevin Zhang, Yichun Shi, Heng Wang, Yiheng Zhu, Guoxian Song, Sizhe An, Janus Kristjansson, Xiao Yang, Matthias Zwicker
论文：https://papers.labml.ai/api/v1/redirect/pdf?paper_key=dc17c424cd1111edb95839eec3084ddd
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