Web: http://arxiv.org/abs/2208.02946

Sept. 23, 2022, 1:15 a.m. | Rundi Wu, Changxi Zheng

cs.CV updates on arXiv.org arxiv.org

Existing generative models for 3D shapes are typically trained on a large 3D
dataset, often of a specific object category. In this paper, we investigate the
deep generative model that learns from only a single reference 3D shape.
Specifically, we present a multi-scale GAN-based model designed to capture the
input shape's geometric features across a range of spatial scales. To avoid
large memory and computational cost induced by operating on the 3D volume, we
build our generator atop the tri-plane …

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