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Empowering Vector Graphics with Consistently Arbitrary Viewing and View-dependent Visibility

2025-05-27 · CVPR 2025 1 · Yidi Li, Jun Xiao, Zhengda Lu, Yiqun Wang, Haiyong Jiang

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.

📄 PDF Abstract BibTeX arXiv:2505.21377

Code (1)

chenxinl/dream3dvg 공식 구현 pytorch

Tasks

3DGSSchedulingVector Graphics

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