用文字生成可缩放的住宅平面图，质量比现有方法高5%。
Text-to-Vector Conversion for Residential Plan Design
- 从文本描述生成带直角的矢量住宅图，支持灵活配置。
- 生成图像在CLIPScore上比现有方法高约5%。
- 新算法将位图平面转为结构化矢量图，质量提升约4%。
计算机图形学包括位图和矢量两种形式，是现代科学、工业和数字通信的基础。位图虽易用，但基于像素的结构限制了缩放能力；矢量图形由数学基元定义，可无限缩放且不失真，但生成更复杂。在设计与建筑领域，矢量图形的灵活性至关重要，尽管计算成本较高。本文提出一种从文本描述生成矢量住宅平面图的新方法，其在基于CLIPScore的视觉质量上较现有方案提升约5%，得益于对直角的天然处理和灵活设置。此外，我们还提出一种新算法，将位图住宅图转化为结构化矢量图像，该图像的CLIPScore相比其他方法提高约4%。
原文摘要 · Abstract (English)
Computer graphics, comprising both raster and vector components, is a fundamental part of modern science, industry, and digital communication. While raster graphics offer ease of use, its pixel-based structure limits scalability. Vector graphics, defined by mathematical primitives, provides scalability without quality loss, however, it is more complex to produce. For design and architecture, the versatility of vector graphics is paramount, despite its computational demands. This paper introduces a novel method for generating vector residential plans from textual descriptions. Our approach surpasses existing solutions by approximately 5% in CLIPScore-based visual quality, benefiting from its inherent handling of right angles and flexible settings. Additionally, we present a new algorithm for vectorizing raster plans into structured vector images. Such images have a better CLIPscore compared to others by about 4%.
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