发表机构
CSSE, Shenzhen University（深圳大学计算机科学与工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对纯文本无输入轮廓的 calligram 生成难题，提出 Telligram 两阶段框架，结合 VSD 与骨架优化等技术，实现从文本提示生成高质量单词级语义 calligram。
AI 中文摘要
紧凑 calligram（文字图案）生成旨在形成语义形状同时保持字母可识别。现有多数方法为形状条件式，主要解决给定轮廓内的下游字母布局问题。本文研究无输入轮廓的纯文本 calligram 生成，该设置难度在于单阶段优化时语义形状形成与字母可读性相互干扰：将单词推向清晰图形易破坏字形结构，保留可读字母则会削弱目标形状。为解决此难题，本文提出 Telligram，一种无训练、低调优的两阶段框架，由语义占用先验形成与可读性约束字形实现构成。第一阶段采用带结构化骨架优化与分层梯度投影的变分分数蒸馏（VSD）生成语义占用先验；第二阶段将该占用先验转换为逐字母区域，通过轻量几何处理重构可读字形布局。该框架可直接从文本提示生成连贯且具创造性的单词级语义 calligram。
英文摘要
Compact calligram generation aims to form a semantic shape while keeping letters recognizable. Most existing methods are shape-conditioned and mainly solve downstream letter layout inside a given contour. We study text-only calligram generation without an input contour. This setting is difficult because semantic shape formation and letter readability strongly interfere with each other when optimized in a single stage. Pushing the word toward a clear figure can easily damage glyph structure, while preserving readable letters can weaken the target shape. To address this difficulty, we present Telligram, a training-free, low-tuning, two-stage framework composed of Semantic Occupancy Prior Formation and Readability-Constrained Glyph Realization. The first stage uses Variational Score Distillation (VSD) with structured skeleton optimization and hierarchical gradient projection to produce a semantic occupancy prior. The second stage converts this occupancy prior into per-letter regions and reconstructs readable glyph layouts through lightweight geometric processing. The framework generates coherent and creative word-level semantic calligrams directly from text prompts.
Comments12 pages, 11 figures, accepted by Computer Graphics Forum / Pacific Graphics 2026
