# ViType: High-Fidelity Visual Text Rendering via Glyph-Aware Multimodal Diffusion

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/vitype-high-fidelity-visual-text-rendering-via-glyph-aware-multimodal-diffusion/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Lishuai Gao,Jun-Yan He,Yingsen Zeng,Yujie Zhong,Xiaopeng Sun,Jie Hu,Zan Gao,Xiaoming Wei |
| Citations | 0 |
| DOI | 10.1609/aaai.v40i6.42408 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1609/aaai.v40i6.42408 |
| OpenAlex ID | https://openalex.org/W7138278618 |
| Type | conference-paper |
| Year | 2026 |

## Paper authors

- [Jie Hu](https://scholariq.org/researchers/jie-hu/)

## Paper primary topic

- [Generative Adversarial Networks and Image Synthesis](https://scholariq.org/topics/generative-adversarial-networks-and-image-synthesis/)

## Paper topics

- [Generative Adversarial Networks and Image Synthesis](https://scholariq.org/topics/generative-adversarial-networks-and-image-synthesis/)
- [Multimodal Machine Learning Applications](https://scholariq.org/topics/multimodal-machine-learning-applications/)
- [Computer Graphics and Visualization Techniques](https://scholariq.org/topics/computer-graphics-and-visualization-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.