Papers › Efficient Geometry-aware 3D Generative Adversarial Networks

Efficient Geometry-aware 3D Generative Adversarial Networks

15 Dec 2021CVPR 2022 1arXiv:2112.07945archive 2025-07-28

Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, Gordon Wetzstein

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 network architecture that, together with other design choices, synthesizes not only high-resolution multi-view-consistent images in real time but also produces high-quality 3D geometry. By decoupling feature generation and neural rendering, our framework is able to leverage state-of-the-art 2D CNN generators, such as StyleGAN2, and inherit their efficiency and expressiveness. We demonstrate state-of-the-art 3D-aware synthesis with FFHQ and AFHQ Cats, among other experiments.

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Syntology Ran 6 of 6 code samples harvested from 1 repository linked to this paper; 0 have no recorded run. Of those that ran: 3 ran · honoured contract; 1 ran · our draft was wrong; 2 ran · fixture could not drive it.

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NVlabs/eg3d officialmentioned in paperpytorchNOASSERTION report

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3ran · honoured contract
1ran · our draft was wrong
2ran · fixture could not drive it

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make_camera_circle_trajectory bruinxiong/EG3D-pytorch/test_eg3d_new.py community (archive-listed) ran · honoured contract fingerprinted licence not identified · pointer only · 7eab0a60cb0840a5 · report
trans_to_img bruinxiong/EG3D-pytorch/test_eg3d_new.py community (archive-listed) ran · fixture could not drive it licence not identified · pointer only · a33ad4be271af223 · report
make_transform identical code first harvested elsewhere ran · fixture could not drive it fingerprinted licence of this copy not recorded · f47dff4b7b27bba7 · report
parse_comma_separated_list identical code first harvested elsewhere ran · our draft was wrong fingerprinted licence of this copy not recorded · d01b68a634f71551 · report
parse_range identical code first harvested elsewhere ran · honoured contract licence of this copy not recorded · f462255138c7700d · report
parse_vec2 identical code first harvested elsewhere ran · honoured contract licence of this copy not recorded · 180016b9227381b1 · report

Tasks

3D geometryComputational EfficiencyNeural Rendering

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Methods

ConvolutionPath Length RegularizationR1 RegularizationWeight Demodulation

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