# VATr++: Choose Your Words Wisely for Handwritten Text Generation

arXiv: https://arxiv.org/abs/2402.10798 · HTML: https://mlsanity.com/paper/2402.10798/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models.
- Builds on 37 of its 66 references that are in the map.
- First posted on arXiv 16 Feb 2024.

## Placed in

- Diffusion models / [Image generation, text-to-image and editing](https://mlsanity.com/diffusion/image-generation-text-to-image-and-editing/)

## Builds on (most cited first, 30 of 37)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Large Scale GAN Training for High Fidelity Natural Image Synthesis](https://mlsanity.com/paper/1809.11096/) (2018)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Training Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2006.06676/) (2020)
- [Generating Sequences With Recurrent Neural Networks](https://mlsanity.com/paper/1308.0850/) (2013)
- [An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition](https://mlsanity.com/paper/1507.05717/) (2015)
- [TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models](https://mlsanity.com/paper/2109.10282/) (2021)
- [Multi-Content GAN for Few-Shot Font Style Transfer](https://mlsanity.com/paper/1712.00516/) (2017)
- [DG-Font: Deformable Generative Networks for Unsupervised Font Generation](https://mlsanity.com/paper/2104.03064/) (2021)
- [ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation](https://mlsanity.com/paper/2003.10557/) (2020)
- [Conditional Text Image Generation with Diffusion Models](https://mlsanity.com/paper/2306.10804/) (2023)
- [Geometry Score: A Method For Comparing Generative Adversarial Networks](https://mlsanity.com/paper/1802.02664/) (2018)
- [Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning](https://mlsanity.com/paper/1910.04987/) (2019)
- [TextStyleBrush: Transfer of Text Aesthetics from a Single Example](https://mlsanity.com/paper/2106.08385/) (2021)
- [Few-shot Font Generation with Localized Style Representations and Factorization](https://mlsanity.com/paper/2009.11042/) (2020)
- [Few-shot Compositional Font Generation with Dual Memory](https://mlsanity.com/paper/2005.10510/) (2020)
- [DeepWriting: Making Digital Ink Editable via Deep Generative Modeling](https://mlsanity.com/paper/1801.08379/) (2018)
- [Adversarial Generation of Handwritten Text Images Conditioned on Sequences](https://mlsanity.com/paper/1903.00277/) (2019)
- [Handwriting Transformers](https://mlsanity.com/paper/2104.03964/) (2021)
- [Text and Style Conditioned GAN for Generation of Offline Handwriting Lines](https://mlsanity.com/paper/2009.00678/) (2020)
- [Content and Style Aware Generation of Text-line Images for Handwriting Recognition](https://mlsanity.com/paper/2204.05539/) (2022)
- [Handwriting Recognition in Low-resource Scripts using Adversarial Learning](https://mlsanity.com/paper/1811.01396/) (2018)
- [Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminator](https://mlsanity.com/paper/2205.00146/) (2022)
- [Handwritten Text Generation from Visual Archetypes](https://mlsanity.com/paper/2303.15269/) (2023)
- [MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition](https://mlsanity.com/paper/2104.01876/) (2021)
- [STCN: Stochastic Temporal Convolutional Networks](https://mlsanity.com/paper/1902.06568/) (2019)
- [SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Text](https://mlsanity.com/paper/2202.11456/) (2022)
- [Diffusion models for Handwriting Generation](https://mlsanity.com/paper/2011.06704/) (2020)
- [Generating Handwriting via Decoupled Style Descriptors](https://mlsanity.com/paper/2008.11354/) (2020)
- [WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models](https://mlsanity.com/paper/2303.16576/) (2023)

## Built on by (most cited first, 18 of 18)

- [Zero-Shot Styled Text Image Generation, but Make It Autoregressive](https://mlsanity.com/paper/2503.17074/) (2025)
- [Handwritten Text Recognition: A Survey](https://mlsanity.com/paper/2502.08417/) (2025)
- [On the Generalization of Handwritten Text Recognition Models](https://mlsanity.com/paper/2411.17332/) (2024)
- [Rethinking HTG Evaluation: Bridging Generation and Recognition](https://mlsanity.com/paper/2409.02683/) (2024)
- [Autoregressive Styled Text Image Generation, but Make it Reliable](https://mlsanity.com/paper/2510.23240/) (2025)
- [Semi-Supervised Adaptation of Diffusion Models for Handwritten Text Generation](https://mlsanity.com/paper/2412.15853/) (2024)
- [Quo Vadis Handwritten Text Generation for Handwritten Text Recognition?](https://mlsanity.com/paper/2508.09936/) (2025)
- [Dual Orthogonal Guidance for Robust Diffusion-based Handwritten Text Generation](https://mlsanity.com/paper/2508.17017/) (2025)
- [CONSTANT: Towards High-Quality One-Shot Handwriting Generation with Patch Contrastive Enhancement and Style-Aware Quantization](https://mlsanity.com/paper/2603.07543/) (2026)
- [Few-shot Writer Adaptation via Multimodal In-Context Learning](https://mlsanity.com/paper/2603.29450/) (2026)
- [Layout Stroke Imitation: A Layout Guided Handwriting Stroke Generation for Style Imitation with Diffusion Model](https://mlsanity.com/paper/2509.15678/) (2025)
- [ScriptViT: Vision Transformer-Based Personalized Handwriting Generation](https://mlsanity.com/paper/2511.18307/) (2025)
- [BeHGAN: Bengali Handwritten Word Generation from Plain Text Using Generative Adversarial Networks](https://mlsanity.com/paper/2512.21694/) (2025)
- [Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies](https://mlsanity.com/paper/2604.09713/) (2026)
- [Diffusion-Based Ukrainian Handwritten Text Generation with Cross-Domain Style Transfer](https://mlsanity.com/paper/2605.27487/) (2026)
- [HandwritingAgent: Language-Driven Handwriting Synthesis in Scalable Vector Space](https://mlsanity.com/paper/2606.18788/) (2026)
- [InkShield: Writing Style Protection Against Unauthorized Handwriting Mimicry](https://mlsanity.com/paper/2607.26976/) (2026)
- [Bridging Online and Offline Handwriting via Differentiable Physical Rendering](https://mlsanity.com/paper/2608.03198/) (2026)

## Abstract (arXiv)

Styled Handwritten Text Generation (HTG) has received significant attention in recent years, propelled by the success of learning-based solutions employing GANs, Transformers, and, preliminarily, Diffusion Models. Despite this surge in interest, there remains a critical yet understudied aspect - the impact of the input, both visual and textual, on the HTG model training and its subsequent influence on performance. This study delves deeper into a cutting-edge Styled-HTG approach, proposing strategies for input preparation and training regularization that allow the model to achieve better performance and generalize better. These aspects are validated through extensive analysis on several different settings and datasets. Moreover, in this work, we go beyond performance optimization and address a significant hurdle in HTG research - the lack of a standardized evaluation protocol. In particular, we propose a standardization of the evaluation protocol for HTG and conduct a comprehensive benchmarking of existing approaches. By doing so, we aim to establish a foundation for fair and meaningful comparisons between HTG strategies, fostering progress in the field.