Learning a Style Space for Interactive Line Drawing Synthesis from Animated 3D Models

Learning a Style Space for Interactive Line Drawing Synthesis from Animated 3D Models
复制标题

DOI:
10.2312/pg.20221237
复制
发表时间:
2022
期刊:
--
影响因子:
--
通讯作者:
Zeyu Wang;Tuanfeng Y. Wang;Julie Dorsey
Zeyu Wang;Tuanfeng Y. Wang;Julie Dorsey
中科院分区:
其他
文献类型:
--
作者:
Zeyu Wang;Tuanfeng Y. Wang;Julie Dorsey

文献摘要

相似文献

大多数非真实感绘制(NPR)方法的线条画合成操作上的静态形状。它们并不适合处理动画3D模型,因为需要进行大量的逐帧参数调整以实现预期的外观和自然过渡。本文介绍了一个框架,交互式线条画合成动画三维模型的基础上学习的风格空间的绘图表示和插值。我们将风格称为线条画中的笔划位置与其相应的几何属性之间的关系。从动画3D角色的给定序列开始,用户为一组关键帧创建绘图。我们的系统嵌入光栅图纸到一个潜在的风格空间后,他们从底层几何解开。通过遍历潜在空间,我们的系统能够实现输入关键帧之间的平滑过渡。用户还可以交互地编辑、添加或移除关键帧,类似于典型的基于关键帧的工作流。我们使用深度神经网络来实现我们的系统,这些神经网络是在NPR方法组合产生的合成线条图上训练的。我们的绘图特定的监督和优化为基础的嵌入机制,允许在运行时从NPR线图用户创建的图纸泛化。实验表明,我们的方法生成高质量的线条画动画,同时允许跨帧的绘画风格的交互式控制。
Most non-photorealistic rendering (NPR) methods for line drawing synthesis operate on a static shape. They are not tailored to process animated 3D models due to extensive per-frame parameter tuning needed to achieve the intended look and natural transition. This paper introduces a framework for interactive line drawing synthesis from animated 3D models based on a learned style space for drawing representation and interpolation. We refer to style as the relationship between stroke placement in a line drawing and its corresponding geometric properties. Starting from a given sequence of an animated 3D character, a user creates drawings for a set of keyframes. Our system embeds the raster drawings into a latent style space after they are disentangled from the underlying geometry. By traversing the latent space, our system enables a smooth transition between the input keyframes. The user may also edit, add, or remove the keyframes interactively, similar to a typical keyframe-based workflow. We implement our system with deep neural networks trained on synthetic line drawings produced by a combination of NPR methods. Our drawing-specific supervision and optimization-based embedding mechanism allow generalization from NPR line drawings to user-created drawings during run time. Experiments show that our approach generates high-quality line drawing animations while allowing interactive control of the drawing style across frames.