  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.
