We present a novel method for the interactive control of geometric
abstraction and texture in artistic images. Previous example-based stylization
methods often entangle shape, texture, and color, while generative methods for
image synthesis generally either make assumptions about the input image, such
as only allowing faces or do not offer precise editing controls. By contrast,
our holistic approach spatially decomposes the input into shapes and a
parametric representation of high-frequency details comprising the image's
texture, thus enabling independent control of color and texture. Each parameter
in this representation controls painterly attributes of a pipeline of
differentiable stylization filters. The proposed decoupling of shape and
texture enables various options for stylistic editing, including interactive
global and local adjustments of shape, stroke, and painterly attributes such as
surface relief and contours. Additionally, we demonstrate optimization-based
texture style-transfer in the parametric space using reference images and text
prompts, as well as the training of single- and arbitrary style parameter
prediction networks for real-time texture decomposition.

我们提出了一种新颖的方法，用于艺术图像中几何抽象和纹理的交互控制。通过空间分解输入图像的形状和高频细节的参数化表示，实现对颜色和纹理的独立控制。所提出的形状和纹理的解耦使得可以进行多种风格编辑，包括形状、笔触和绘画属性等的全局和局部互动调整。此外，我们还展示了在参数空间中使用参考图像和文本提示进行基于优化的纹理风格迁移，以及用于实时纹理分解的单一和任意风格参数预测网络的训练。