Learning to Generate Poetic Chinese Landscape Painting with Calligraphy
Shaozu Yuan, Aijun Dai, Zhiling Yan, Ruixue Liu, Meng Chen, Baoyang, Chen, Zhijie Qiu, Xiaodong He

TL;DR
This paper introduces Polaca, a system that generates poetic Chinese landscape paintings with calligraphy from poetry, combining text-to-image, style transfer, and image fusion modules for artistic creation.
Contribution
The paper presents a novel multi-module system for generating integrated Chinese landscape paintings with calligraphy from poetry, advancing AI art generation techniques.
Findings
Successful generation of landscape images from poetry
Effective fusion of landscape and calligraphy images
Enhanced aesthetic quality of the generated artworks
Abstract
In this paper, we present a novel system (denoted as Polaca) to generate poetic Chinese landscape painting with calligraphy. Unlike previous single image-to-image painting generation, Polaca takes the classic poetry as input and outputs the artistic landscape painting image with the corresponding calligraphy. It is equipped with three different modules to complete the whole piece of landscape painting artwork: the first one is a text-to-image module to generate landscape painting image, the second one is an image-to-image module to generate stylistic calligraphy image, and the third one is an image fusion module to fuse the two images into a whole piece of aesthetic artwork.
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · Advanced Image and Video Retrieval Techniques · 3D Surveying and Cultural Heritage
