Abstract
This work presents a novel text-to-vector graphics generation approach, Dream3DVG, allowing for arbitrary viewpoint viewing, progressive detail optimization, and view-dependent occlusion awareness. Our approach is a dual-branch optimization framework, consisting of an auxiliary 3D Gaussian Splatting optimization branch and a 3D vector graphics optimization branch. The introduced 3DGS branch can bridge the domain gaps between text prompts and vector graphics with more consistent guidance. Moreover, 3DGS allows for progressive detail control by scheduling classifier-free guidance, facilitating guiding vector graphics with coarse shapes at the initial stages and finer details at later stages. We also improve the view-dependent occlusions by devising a visibility-awareness rendering module. Extensive results on 3D sketches and 3D iconographies, demonstrate the superiority of the method on different abstraction levels of details, cross-view consistency, and occlusion-aware stroke culling.
Abstract (translated)
这项工作提出了一种新颖的文本到矢量图形生成方法，名为Dream3DVG，该方法允许任意视角查看、渐进式细节优化以及视图依赖性遮挡感知。我们的方法是一个双分支优化框架，包含一个辅助的3D高斯点置射优化学派和一个3D矢量图形优化学派。引入的3DGS分支可以弥合文本提示与矢量图形之间的领域差距，并提供更一致的指导。此外，3DGS通过调度无分类器引导，允许渐进式细节控制，在初始阶段用粗略形状进行矢量图形引导，在后续阶段添加更多细节。我们还改进了视图依赖性遮挡问题，设计了一个可见性感知渲染模块。在3D草图和3D图标上的大量实验结果表明，该方法在不同抽象层次的细节、跨视角一致性以及基于视图遮挡的笔触剔除方面具有明显优势。
URL
https://arxiv.org/abs/2505.21377
