用双参数化让画笔绘制又快又准，结构更清晰。
Differentiable Stroke Planning with Dual Parameterization for Efficient and High-Fidelity Painting Creation
- 用折线和贝塞尔点双向绑定，兼顾离散与连续优势
- 少用30%-50%画笔数，重建质量更高，提速30%-40%
- 适合需要高效高质量矢量绘画的创意工具开发者
在基于画笔的渲染中，搜索方法常因画笔离散布局陷入局部最优，而可微优化器缺乏结构感知，生成杂乱布局。为此，我们提出一种双表示机制，通过双向映射将离散折线与连续贝塞尔控制点耦合，实现协同优化：局部梯度优化全局结构，内容感知的画笔提案帮助跳出劣质局部极小值。该表示还支持类高斯点云初始化，实现图像层面的高并行画笔优化。实验表明，本方法使画笔数量减少30%-50%，布局更结构化，重建质量提升，优化时间较现有可微矢量化方法缩短30%-40%。
原文摘要 · Abstract (English)
In stroke-based rendering, search methods often get trapped in local minima due to discrete stroke placement, while differentiable optimizers lack structural awareness and produce unstructured layouts. To bridge this gap, we propose a dual representation that couples discrete polylines with continuous Bézier control points via a bidirectional mapping mechanism. This enables collaborative optimization: local gradients refine global stroke structures, while content-aware stroke proposals help escape poor local optima. Our representation further supports Gaussian-splatting-inspired initialization, enabling highly parallel stroke optimization across the image. Experiments show that our approach reduces the number of strokes by 30-50%, achieves more structurally coherent layouts, and improves reconstruction quality, while cutting optimization time by 30-40% compared to existing differentiable vectorization methods.
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