# Controllable Artistic Text Style Transfer via Shape-Matching GAN

arXiv: https://arxiv.org/abs/1905.01354 · HTML: https://mlsanity.com/paper/1905.01354/

## Key facts

- Cited by 45 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 May 2019.

## Built on by (most cited first, 30 of 45)

- [Versatile Diffusion: Text, Images and Variations All in One Diffusion Model](https://mlsanity.com/paper/2211.08332/) (2022)
- [TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up](https://mlsanity.com/paper/2102.07074/) (2021)
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- [Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training](https://mlsanity.com/paper/2111.01118/) (2021)
- [FonTS: Text Rendering with Typography and Style Controls](https://mlsanity.com/paper/2412.00136/) (2024)
- [Exploring Stroke-Level Modifications for Scene Text Editing](https://mlsanity.com/paper/2212.01982/) (2022)
- [Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training](https://mlsanity.com/paper/2204.02844/) (2022)
- [SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Text](https://mlsanity.com/paper/2202.11456/) (2022)
- [De-rendering Stylized Texts](https://mlsanity.com/paper/2110.01890/) (2021)
- [RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmark](https://mlsanity.com/paper/2201.00466/) (2022)
- [Bi-LORA: A Vision-Language Approach for Synthetic Image Detection](https://mlsanity.com/paper/2404.01959/) (2024)
- [Geometry Transfer for Stylizing Radiance Fields](https://mlsanity.com/paper/2402.00863/) (2024)
- [WordCon: Word-level Typography Control in Scene Text Rendering](https://mlsanity.com/paper/2506.21276/) (2025)
- [STRIVE: Scene Text Replacement In Videos](https://mlsanity.com/paper/2109.02762/) (2021)
- [Texture Reformer: Towards Fast and Universal Interactive Texture Transfer](https://mlsanity.com/paper/2112.02788/) (2021)
- [Towards Diverse and Consistent Typography Generation](https://mlsanity.com/paper/2309.02099/) (2023)
- [SGBANet: Semantic GAN and Balanced Attention Network for Arbitrarily Oriented Scene Text Recognition](https://mlsanity.com/paper/2207.10256/) (2022)
- [Industrial Style Transfer with Large-scale Geometric Warping and Content Preservation](https://mlsanity.com/paper/2203.12835/) (2022)
- [FontStudio: Shape-Adaptive Diffusion Model for Coherent and Consistent Font Effect Generation](https://mlsanity.com/paper/2406.08392/) (2024)
- [Kinetic Typography Diffusion Model](https://mlsanity.com/paper/2407.10476/) (2024)
- [Intelligent Artistic Typography: A Comprehensive Review of Artistic Text Design and Generation](https://mlsanity.com/paper/2407.14774/) (2024)
- [GenText: Unsupervised Artistic Text Generation via Decoupled Font and Texture Manipulation](https://mlsanity.com/paper/2207.09649/) (2022)
- [FASTER: A Font-Agnostic Scene Text Editing and Rendering Framework](https://mlsanity.com/paper/2308.02905/) (2023)
- [On Manipulating Scene Text in the Wild with Diffusion Models](https://mlsanity.com/paper/2311.00734/) (2023)
- [OmniPrint: A Configurable Printed Character Synthesizer](https://mlsanity.com/paper/2201.06648/) (2022)
- [VQ-Font: Few-Shot Font Generation with Structure-Aware Enhancement and Quantization](https://mlsanity.com/paper/2308.14018/) (2023)
- [Sparse Mixture Once-for-all Adversarial Training for Efficient In-Situ Trade-Off Between Accuracy and Robustness of DNNs](https://mlsanity.com/paper/2302.03523/) (2022)
- [Coarse-to-Fine Searching for Efficient Generative Adversarial Networks](https://mlsanity.com/paper/2104.09223/) (2021)
- [Black-Box Diagnosis and Calibration on GAN Intra-Mode Collapse: A Pilot Study](https://mlsanity.com/paper/2107.12202/) (2021)
- [APRNet: Attention-based Pixel-wise Rendering Network for Photo-Realistic Text Image Generation](https://mlsanity.com/paper/2203.07705/) (2022)

## Abstract (arXiv)

Artistic text style transfer is the task of migrating the style from a source image to the target text to create artistic typography. Recent style transfer methods have considered texture control to enhance usability. However, controlling the stylistic degree in terms of shape deformation remains an important open challenge. In this paper, we present the first text style transfer network that allows for real-time control of the crucial stylistic degree of the glyph through an adjustable parameter. Our key contribution is a novel bidirectional shape matching framework to establish an effective glyph-style mapping at various deformation levels without paired ground truth. Based on this idea, we propose a scale-controllable module to empower a single network to continuously characterize the multi-scale shape features of the style image and transfer these features to the target text. The proposed method demonstrates its superiority over previous state-of-the-arts in generating diverse, controllable and high-quality stylized text.