Assisting people in efficiently producing visually plausible 3D characters has always been a fundamental research topic in computer vision and computer graphics. Recent learning-based approaches have achieved unprecedented accuracy and efficiency in the area of 3D real human digitization. However, none of the prior works focus on modeling 3D biped cartoon characters, which are also in great demand in gaming and filming. In this paper, we introduce 3DBiCar, the first large-scale dataset of 3D biped cartoon characters, and RaBit, the corresponding parametric model. Our dataset contains 1,500 topologically consistent high-quality 3D textured models which are manually crafted by professional artists. Built upon the data, RaBit is thus designed with a SMPL-like linear blend shape model and a StyleGAN-based neural UV-texture generator, simultaneously expressing the shape, pose, and texture. To demonstrate the practicality of 3DBiCar and RaBit, various applications are conducted, including single-view reconstruction, sketch-based modeling, and 3D cartoon animation. For the single-view reconstruction setting, we find a straightforward global mapping from input images to the output UV-based texture maps tends to lose detailed appearances of some local parts (e.g., nose, ears). Thus, a part-sensitive texture reasoner is adopted to make all important local areas perceived. Experiments further demonstrate the effectiveness of our method both qualitatively and quantitatively. 3DBiCar and RaBit are available at gaplab.cuhk.edu.cn/projects/RaBit.

翻译：协助人们高效生成视觉上可信的三维角色，始终是计算机视觉与计算机图形学领域的基础研究课题。近年来，基于学习的方法在三维真实人体数字化方面取得了前所未有的精度与效率。然而，现有研究均未关注三维双足卡通角色的建模，而此类角色在游戏与影视制作中需求巨大。本文首次提出大规模三维双足卡通角色数据集3DBiCar及其对应的参数化模型RaBit。该数据集包含1500个拓扑一致的高质量三维纹理模型，均由专业艺术家手工制作。基于此数据，RaBit设计了类似SMPL的线性融合形状模型与基于StyleGAN的神经UV纹理生成器，同步表达形状、姿态与纹理。为验证3DBiCar与RaBit的实用性，我们开展了多项应用，包括单视图重建、草图建模及三维卡通动画。针对单视图重建任务，我们发现从输入图像到输出UV纹理图的直接全局映射容易丢失局部区域（如鼻子、耳朵）的细节外观。因此，我们采用部件敏感纹理推理器，使所有重要局部区域得到有效感知。实验从定性及定量两方面进一步验证了方法的有效性。3DBiCar与RaBit可访问 gaplab.cuhk.edu.cn/projects/RaBit。