Creating the photo-realistic version of people sketched portraits is useful to various entertainment purposes. Existing studies only generate portraits in the 2D plane with fixed views, making the results less vivid. In this paper, we present Stereoscopic Simplified Sketch-to-Portrait (SSSP), which explores the possibility of creating Stereoscopic 3D-aware portraits from simple contour sketches by involving 3D generative models. Our key insight is to design sketch-aware constraints that can fully exploit the prior knowledge of a tri-plane-based 3D-aware generative model. Specifically, our designed region-aware volume rendering strategy and global consistency constraint further enhance detail correspondences during sketch encoding. Moreover, in order to facilitate the usage of layman users, we propose a Contour-to-Sketch module with vector quantized representations, so that easily drawn contours can directly guide the generation of 3D portraits. Extensive comparisons show that our method generates high-quality results that match the sketch. Our usability study verifies that our system is greatly preferred by user.

翻译：从简化的人物素描生成逼真的照片级肖像对多种娱乐场景具有实用价值。现有研究仅能在固定视角的二维平面上生成肖像，导致结果缺乏生动性。本文提出立体简化素描到肖像生成方法（Stereoscopic Simplified Sketch-to-Portrait, SSSP），通过引入三维生成模型探索从简单轮廓素描创建三维感知立体肖像的可能性。我们的关键洞察是设计素描感知约束，以充分挖掘基于三平面的三维生成模型的先验知识。具体而言，我们设计了区域感知体渲染策略与全局一致性约束，以增强素描编码过程中的细节对应关系。此外，为方便普通用户使用，我们提出基于向量量化表征的轮廓到素描模块，使易于绘制的轮廓可直接引导三维肖像生成。广泛对比表明，本方法可生成与素描匹配的高质量结果。可用性研究证实，用户对本系统具有显著偏好。