Efficient Geometry-aware 3D Generative Adversarial Networks. (arXiv:2112.07945v2 [cs.CV] UPDATED)

Unsupervised generation of high-quality multi-view-consistent images and 3D
shapes using only collections of single-view 2D photographs has been a
long-standing challenge. Existing 3D GANs are either compute-intensive or make
approximations that are not 3D-consistent; the former limits quality and
resolution of the generated images and the latter adversely affects multi-view
consistency and shape quality. In this work, we improve the computational
efficiency and image quality of 3D GANs without overly relying on these
approximations. We introduce an expressive hybrid explicit-implicit …

3d arxiv cv generative adversarial networks geometry networks