# CalliPaint: Chinese Calligraphy Inpainting with Diffusion Model

arXiv: https://arxiv.org/abs/2312.01536 · HTML: https://mlsanity.com/paper/2312.01536/

## Key facts

- Cited by 4 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 4 of its 5 references that are in the map.
- First posted on arXiv 3 Dec 2023.

## 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, 4 of 4)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [CalliGAN: Style and Structure-aware Chinese Calligraphy Character Generator](https://mlsanity.com/paper/2005.12500/) (2020)
- [ZiGAN: Fine-grained Chinese Calligraphy Font Generation via a Few-shot Style Transfer Approach](https://mlsanity.com/paper/2108.03596/) (2021)
- [Calliffusion: Chinese Calligraphy Generation and Style Transfer with Diffusion Modeling](https://mlsanity.com/paper/2305.19124/) (2023)

## Built on by (most cited first, 4 of 4)

- [CalliffusionV2: Personalized Natural Calligraphy Generation with Flexible Multi-modal Control](https://mlsanity.com/paper/2410.03787/) (2024)
- [UniCalli: A Unified Diffusion Framework for Column-Level Generation and Recognition of Chinese Calligraphy](https://mlsanity.com/paper/2510.13745/) (2025)
- [Machine Apophenia: The Kaleidoscopic Generation of Architectural Images](https://mlsanity.com/paper/2407.09172/) (2024)
- [CalliMaster: Mastering Page-level Chinese Calligraphy via Layout-guided Spatial Planning](https://mlsanity.com/paper/2603.12482/) (2026)

## Abstract (arXiv)

Chinese calligraphy can be viewed as a unique form of visual art. Recent advancements in computer vision hold significant potential for the future development of generative models in the realm of Chinese calligraphy. Nevertheless, methods of Chinese calligraphy inpainting, which can be effectively used in the art and education fields, remain relatively unexplored. In this paper, we introduce a new model that harnesses recent advancements in both Chinese calligraphy generation and image inpainting. We demonstrate that our proposed model CalliPaint can produce convincing Chinese calligraphy.