dailenson/SDT

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1403 stars · 113 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official PyTorch implementation of the CVPR 2023 paper 'Disentangling Writer and Character Styles for Handwriting Generation' (SDT). It generates online handwriting with conditional content and style by disentangling writer-wise and character-wise style representations using a style-disentangled Transformer.

Use cases

• generate handwriting in a specific person's style
• synthesize online Chinese handwriting with stroke order
• disentangle writer style from character style in handwriting
• generate offline Chinese handwriting images
• research handwriting generation models
• create custom-styled handwritten text samples

When to choose

• you need to generate handwriting imitating a specific writer's style
• you want a research-grade model for online handwriting with stroke order
• you need Chinese handwriting synthesis with disentangled style control

When to avoid

• you need production-ready handwriting OCR or recognition
• you need full-line English text generation without adaptation
• you want a plug-and-play tool with no ML setup

Facets

library · maturity active

deep-learning machine-learning image-processing data-generation computer-vision deep-learning python handwriting-generation style-disentanglement transformer contrastive-learning cvpr-2023 chinese-handwriting online-handwriting research-code natural-language-processing linux gpu

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