论文标题
Dr.3d：将3D甘套调整为艺术图纸
Dr.3D: Adapting 3D GANs to Artistic Drawings
论文作者
论文摘要
尽管3D GAN最近证明了多视图一致的图像和3D形状的高质量合成，但它们主要仅限于照片现实的人类肖像。本文的目的是将3D甘斯扩展到一种不同但有意义的视觉形式：艺术肖像画。但是，由于图纸中存在不可避免的几何模棱两可，将现有的3D甘斯扩展到图纸是具有挑战性的。为了解决这个问题，我们介绍了Dr.3d，这是一种新颖的适应方法，可将现有的3D GAN适应艺术图。 Dr.3d配备了三个新的组件来处理几何歧义：变形感知3D合成网络，姿势估计和图像合成的交替适应以及几何学先验。实验表明，我们的方法可以成功地适应3D gans图纸，并使多视图一致的绘画语义编辑。
While 3D GANs have recently demonstrated the high-quality synthesis of multi-view consistent images and 3D shapes, they are mainly restricted to photo-realistic human portraits. This paper aims to extend 3D GANs to a different, but meaningful visual form: artistic portrait drawings. However, extending existing 3D GANs to drawings is challenging due to the inevitable geometric ambiguity present in drawings. To tackle this, we present Dr.3D, a novel adaptation approach that adapts an existing 3D GAN to artistic drawings. Dr.3D is equipped with three novel components to handle the geometric ambiguity: a deformation-aware 3D synthesis network, an alternating adaptation of pose estimation and image synthesis, and geometric priors. Experiments show that our approach can successfully adapt 3D GANs to drawings and enable multi-view consistent semantic editing of drawings.
