Abstract
Creating a stroke-by-stroke evolution process of a visual artwork tries to bridge the emotional and educational gap between the finished static artwork and its creation process. Recent stroke-based painting systems focus on capturing stroke details by predicting and iteratively refining stroke parameters to maximize the similarity between the input image and the rendered output. However, these methods often struggle to produce stroke compositions that align with artistic principles and intent. To address this, we explore an image-to-painting method that (i) facilitates semantic guidance for brush strokes in targeted regions, (ii) computes the brush stroke parameters, and (iii) establishes a sequence among segments and strokes to sequentially render the final painting. Experimental results on various input image types, such as face images, paintings, and photographic images, show that our method aligns with a region-based painting strategy while rendering a painting with high fidelity and superior stroke quality.
Abstract (translated)
创建一幅视觉艺术品的笔触演变过程旨在弥合最终静态作品与其创作过程之间的情感和教育差距。最近的基于笔触的绘画系统专注于通过预测并迭代细化笔触参数来捕捉笔触细节，以最大限度地提高输入图像与渲染输出之间的相似性。然而，这些方法往往难以生成符合艺术原则和意图的笔触组合。为了解决这一问题，我们探索了一种将图像转化为绘画的方法，该方法： (i) 在目标区域提供语义指导给笔触； (ii) 计算刷子笔触参数； (iii) 建立段落和笔触之间的顺序以逐步渲染最终画作。 在各种输入图像类型上的实验结果（如人脸图像、油画和摄影作品）显示，我们的方法符合基于区域的绘画策略，并能高保真度地渲染出高质量笔触的作品。
URL
https://arxiv.org/abs/2506.09969
