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We propose PAniC-3D, a system to reconstruct stylized 3D character headsdirectly from illustrated (p)ortraits of (ani)me (c)haracters. Our anime-styledomain poses unique challenges to single-view reconstruction; compared tonatural images of human heads, character portrait illustrations have hair andaccessories with more complex and diverse geometry, and are shaded withnon-photorealistic contour lines. In addition, there is a lack of both 3D modeland portrait illustration data suitable to train and evaluate this ambiguousstylized reconstruction task. Facing these challenges, our proposed PAniC-3Darchitecture crosses the illustration-to-3D domain gap with a line-fillingmodel, and represents sophisticated geometries with a volumetric radiancefield. We train our system with two large new datasets (11.2k Vroid 3D models,1k Vtuber portrait illustrations), and evaluate on a novel AnimeRecon benchmarkof illustration-to-3D pairs. PAniC-3D significantly outperforms baselinemethods, and provides data to establish the task of stylized reconstructionfrom portrait illustrations.

PAniC-3D: Stylized Single-view 3D Reconstruction from Portraits of Anime Characters