Neural Image Abstraction Using Long Smoothing B-Splines

📝 Original Info

• Title: Neural Image Abstraction Using Long Smoothing B-Splines
• ArXiv ID: 2511.05360
• Date: 2025-11-07
• Authors: ** 논문에 명시된 저자 정보가 제공되지 않았습니다. (저자명, 소속, 연락처 등은 원문을 확인해 주세요.) **

📝 Abstract

We integrate smoothing B-splines into a standard differentiable vector graphics (DiffVG) pipeline through linear mapping, and show how this can be used to generate smooth and arbitrarily long paths within image-based deep learning systems. We take advantage of derivative-based smoothing costs for parametric control of fidelity vs. simplicity tradeoffs, while also enabling stylization control in geometric and image spaces. The proposed pipeline is compatible with recent vector graphics generation and vectorization methods. We demonstrate the versatility of our approach with four applications aimed at the generation of stylized vector graphics: stylized space-filling path generation, stroke-based image abstraction, closed-area image abstraction, and stylized text generation.

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