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GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Images. (arXiv:2209.11163v1 [cs.CV])
Sept. 23, 2022, 1:15 a.m. | Jun Gao, Tianchang Shen, Zian Wang, Wenzheng Chen, Kangxue Yin, Daiqing Li, Or Litany, Zan Gojcic, Sanja Fidler
cs.CV updates on arXiv.org arxiv.org
As several industries are moving towards modeling massive 3D virtual worlds,
the need for content creation tools that can scale in terms of the quantity,
quality, and diversity of 3D content is becoming evident. In our work, we aim
to train performant 3D generative models that synthesize textured meshes which
can be directly consumed by 3D rendering engines, thus immediately usable in
downstream applications. Prior works on 3D generative modeling either lack
geometric details, are limited in the mesh topology …
More from arxiv.org / cs.CV updates on arXiv.org
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