mlsanityData to 7 Oct 2026

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

arXiv 2402.10798 ↗First posted 16 Feb 2024cs.CV cs.AIcited by 18

On the map: Diffusion models → Image generation, text-to-image and editing

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.

Key facts. Cited by 18 papers in the map (data through 7 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.

Builds on

37 of 66 references.

Closest ancestors · 4

Same direction, newest first

  1. 2023Conditional Text Image Generation with Diffusion Models19 Jun
  2. 2023Improving Handwritten OCR with Training Samples Generated by Glyph Conditional Denoising Diffusion Probabilistic Model31 May
  3. 2023WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models29 Mar
  4. 2020Diffusion models for Handwriting Generation13 Nov

Other references · 33

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  3. 2014Conditional Generative Adversarial Netscited by 2,152
  4. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  5. 2013Generating Sequences With Recurrent Neural Networkscited by 549
  6. 2015An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognitioncited by 519
  7. 2021TrOCR: Transformer-based Optical Character Recognition with Pre-trained Modelscited by 278
  8. 2017Multi-Content GAN for Few-Shot Font Style Transfercited by 100
  9. 2021DG-Font: Deformable Generative Networks for Unsupervised Font Generationcited by 70
  10. 2020ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generationcited by 69
  11. 2018Geometry Score: A Method For Comparing Generative Adversarial Networkscited by 56
  12. 2019Artistic Glyph Image Synthesis via One-Stage Few-Shot Learningcited by 53
21 more
  1. 2021TextStyleBrush: Transfer of Text Aesthetics from a Single Examplecited by 48
  2. 2020Few-shot Font Generation with Localized Style Representations and Factorizationcited by 47
  3. 2020Few-shot Compositional Font Generation with Dual Memorycited by 44
  4. 2018DeepWriting: Making Digital Ink Editable via Deep Generative Modelingcited by 39
  5. 2019Adversarial Generation of Handwritten Text Images Conditioned on Sequencescited by 37
  6. 2021Handwriting Transformerscited by 37
  7. 2020Text and Style Conditioned GAN for Generation of Offline Handwriting Linescited by 35
  8. 2022Content and Style Aware Generation of Text-line Images for Handwriting Recognitioncited by 35
  9. 2018Handwriting Recognition in Low-resource Scripts using Adversarial Learningcited by 32
  10. 2022Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminatorcited by 32
  11. 2023Handwritten Text Generation from Visual Archetypescited by 32
  12. 2021MetaHTR: Towards Writer-Adaptive Handwritten Text Recognitioncited by 27
  13. 2019STCN: Stochastic Temporal Convolutional Networkscited by 26
  14. 2022SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Textcited by 26
  15. 2020Generating Handwriting via Decoupled Style Descriptorscited by 23
  16. 2018Generating Handwritten Chinese Characters using CycleGANcited by 21
  17. 2023HWD: A Novel Evaluation Score for Styled Handwritten Text Generationcited by 19
  18. 2021Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillationcited by 17
  19. 2019Generative Adversarial Network for Handwritten Textcited by 12
  20. 2022SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generationcited by 6
  21. 2021Generating Synthetic Handwritten Historical Documents With OCR Constrained GANscited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 7.

18 papers.

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  1. 2025Zero-Shot Styled Text Image Generation, but Make It Autoregressivecited by 13
  2. 2025Handwritten Text Recognition: A Surveycited by 12
  3. 2024On the Generalization of Handwritten Text Recognition Modelscited by 10
  4. 2024Rethinking HTG Evaluation: Bridging Generation and Recognitioncited by 6
  5. 2025Autoregressive Styled Text Image Generation, but Make it Reliablecited by 3
  6. 2024Semi-Supervised Adaptation of Diffusion Models for Handwritten Text Generationcited by 2
  7. 2025Quo Vadis Handwritten Text Generation for Handwritten Text Recognition?cited by 2
  8. 2025Dual Orthogonal Guidance for Robust Diffusion-based Handwritten Text Generationcited by 2
  9. 2026CONSTANT: Towards High-Quality One-Shot Handwriting Generation with Patch Contrastive Enhancement and Style-Aware Quantizationcited by 1
  10. 2026Few-shot Writer Adaptation via Multimodal In-Context Learningcited by 1
  11. 2025Layout Stroke Imitation: A Layout Guided Handwriting Stroke Generation for Style Imitation with Diffusion Modelcited by 0
  12. 2025ScriptViT: Vision Transformer-Based Personalized Handwriting Generationcited by 0
6 more
  1. 2025BeHGAN: Bengali Handwritten Word Generation from Plain Text Using Generative Adversarial Networkscited by 0
  2. 2026Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogiescited by 0
  3. 2026Diffusion-Based Ukrainian Handwritten Text Generation with Cross-Domain Style Transfercited by 0
  4. 2026HandwritingAgent: Language-Driven Handwriting Synthesis in Scalable Vector Spacecited by 0
  5. 2026InkShield: Writing Style Protection Against Unauthorized Handwriting Mimicrycited by 0
  6. 2026Bridging Online and Offline Handwriting via Differentiable Physical Renderingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024DiffusionPen: Towards Controlling the Style of Handwritten Text Generation
  2. 2023StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis
  3. 2025Advancing Offline Handwritten Text Recognition: A Systematic Review of Data Augmentation and Generation Techniques
  4. 2025Text-Conditioned Diffusion Model for High-Fidelity Korean Font Generation
  5. 2025NeuralSVG: An Implicit Representation for Text-to-Vector Generation
  6. 2024Text-to-Image Synthesis: A Decade Survey
  7. 2024Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation
  8. 2024StylusAI: Stylistic Adaptation for Robust German Handwritten Text Generation