# HWD: A Novel Evaluation Score for Styled Handwritten Text Generation

arXiv: https://arxiv.org/abs/2310.20316 · HTML: https://mlsanity.com/paper/2310.20316/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 44 references that are in the map.
- First posted on arXiv 31 Oct 2023.

## Builds on (most cited first, 22 of 22)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Effectively Unbiased FID and Inception Score and where to find them](https://mlsanity.com/paper/1911.07023/) (2019)
- [ScrabbleGAN: Semi-Supervised Varying Length Handwritten Text Generation](https://mlsanity.com/paper/2003.10557/) (2020)
- [GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images](https://mlsanity.com/paper/2003.02567/) (2020)
- [Geometry Score: A Method For Comparing Generative Adversarial Networks](https://mlsanity.com/paper/1802.02664/) (2018)
- [Rethinking and Improving the Robustness of Image Style Transfer](https://mlsanity.com/paper/2104.05623/) (2021)
- [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)
- [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)
- [SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Text](https://mlsanity.com/paper/2202.11456/) (2022)
- [SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators](https://mlsanity.com/paper/2105.10528/) (2021)
- [Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillation](https://mlsanity.com/paper/2107.12087/) (2021)
- [The LAM Dataset: A Novel Benchmark for Line-Level Handwritten Text Recognition](https://mlsanity.com/paper/2208.07682/) (2022)
- [Boosting Modern and Historical Handwritten Text Recognition with Deformable Convolutions](https://mlsanity.com/paper/2208.08109/) (2022)
- [How to Choose Pretrained Handwriting Recognition Models for Single Writer Fine-Tuning](https://mlsanity.com/paper/2305.02593/) (2023)
- [BanglaWriting: A multi-purpose offline Bangla handwriting dataset](https://mlsanity.com/paper/2011.07499/) (2020)
- [Evaluating Synthetic Pre-Training for Handwriting Processing Tasks](https://mlsanity.com/paper/2304.01842/) (2023)

## Built on by (most cited first, 19 of 19)

- [VATr++: Choose Your Words Wisely for Handwritten Text Generation](https://mlsanity.com/paper/2402.10798/) (2024)
- [Zero-Shot Styled Text Image Generation, but Make It Autoregressive](https://mlsanity.com/paper/2503.17074/) (2025)
- [Beyond Isolated Words: Diffusion Brush for Handwritten Text-Line Generation](https://mlsanity.com/paper/2508.03256/) (2025)
- [Rethinking HTG Evaluation: Bridging Generation and Recognition](https://mlsanity.com/paper/2409.02683/) (2024)
- [Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models](https://mlsanity.com/paper/2409.00786/) (2024)
- [Autoregressive Styled Text Image Generation, but Make it Reliable](https://mlsanity.com/paper/2510.23240/) (2025)
- [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)
- [FW-GAN: Frequency-Driven Handwriting Synthesis with Wave-Modulated MLP Generator](https://mlsanity.com/paper/2508.21040/) (2025)
- [SkyReels-Text: Fine-Grained Font-Controllable Text Editing for Poster Design](https://mlsanity.com/paper/2511.13285/) (2025)
- [Shifting the Breaking Point of Flow Matching for Multi-Instance Editing](https://mlsanity.com/paper/2602.08749/) (2026)
- [CONSTANT: Towards High-Quality One-Shot Handwriting Generation with Patch Contrastive Enhancement and Style-Aware Quantization](https://mlsanity.com/paper/2603.07543/) (2026)
- [A Text Recognition Dataset from Sahidic Coptic Ancient Manuscripts](https://mlsanity.com/paper/2606.15987/) (2026)
- [GAN-based Content-Conditioned Generation of Handwritten Musical Symbols](https://mlsanity.com/paper/2510.17869/) (2025)
- [ScriptViT: Vision Transformer-Based Personalized Handwriting Generation](https://mlsanity.com/paper/2511.18307/) (2025)
- [HandwritingAgent: Language-Driven Handwriting Synthesis in Scalable Vector Space](https://mlsanity.com/paper/2606.18788/) (2026)
- [SpiS-GAN: Spiral-Modulated Handwriting Synthesis with Star Operation](https://mlsanity.com/paper/2607.06949/) (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 (Styled HTG) is an important task in document analysis, aiming to generate text images with the handwriting of given reference images. In recent years, there has been significant progress in the development of deep learning models for tackling this task. Being able to measure the performance of HTG models via a meaningful and representative criterion is key for fostering the development of this research topic. However, despite the current adoption of scores for natural image generation evaluation, assessing the quality of generated handwriting remains challenging. In light of this, we devise the Handwriting Distance (HWD), tailored for HTG evaluation. In particular, it works in the feature space of a network specifically trained to extract handwriting style features from the variable-lenght input images and exploits a perceptual distance to compare the subtle geometric features of handwriting. Through extensive experimental evaluation on different word-level and line-level datasets of handwritten text images, we demonstrate the suitability of the proposed HWD as a score for Styled HTG. The pretrained model used as backbone will be released to ease the adoption of the score, aiming to provide a valuable tool for evaluating HTG models and thus contributing to advancing this important research area.