基于区域的向量化笔触生成，让艺术渲染更符合创作意图。
Vectorized Region Based Brush Strokes for Artistic Rendering
- 按区域提供语义引导，精准控制笔触分布
- 生成高保真画作，笔触质量优于现有方法
- 适合艺术创作、数字绘画领域研究者使用
逐笔生成视觉艺术作品的演化过程，有助于弥合静态完成作品与其创作过程之间的情感与教育鸿沟。现有基于笔触的绘画系统通过预测并迭代优化笔触参数，以最大化输入图像与渲染结果之间的相似性，但常难以生成符合艺术原则和创作意图的笔触组合。为此，本文提出一种图像到绘画的方法，(i) 在目标区域为笔触提供语义引导，(ii) 计算笔触参数，(iii) 建立笔触段落间的顺序关系，实现分步渲染最终画作。在人脸、绘画和照片等多种输入图像上的实验表明，该方法能有效遵循区域化绘画策略，在保持高保真度的同时，显著提升笔触质量。
原文摘要 · Abstract (English)
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.
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