# Learning to Generate Poetic Chinese Landscape Painting with Calligraphy

arXiv: https://arxiv.org/abs/2305.04719 · HTML: https://mlsanity.com/paper/2305.04719/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 31 references that are in the map.
- First posted on arXiv 8 May 2023.

## Builds on (most cited first, 12 of 12)

- [Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks](https://mlsanity.com/paper/1506.01497/) (2015)
- [Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling](https://mlsanity.com/paper/1412.3555/) (2014)
- [CogView: Mastering Text-to-Image Generation via Transformers](https://mlsanity.com/paper/2105.13290/) (2021)
- [AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks](https://mlsanity.com/paper/1711.10485/) (2017)
- [Bidirectional LSTM-CRF Models for Sequence Tagging](https://mlsanity.com/paper/1508.01991/) (2015)
- [U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation](https://mlsanity.com/paper/1907.10830/) (2019)
- [Separating Style and Content for Generalized Style Transfer](https://mlsanity.com/paper/1711.06454/) (2017)
- [Chinese Poetry Generation with Planning based Neural Network](https://mlsanity.com/paper/1610.09889/) (2016)
- [End-to-End Chinese Landscape Painting Creation Using Generative Adversarial Networks](https://mlsanity.com/paper/2011.05552/) (2020)
- [Art2Real: Unfolding the Reality of Artworks via Semantically-Aware Image-to-Image Translation](https://mlsanity.com/paper/1811.10666/) (2018)
- [Robust Real-World Image Super-Resolution against Adversarial Attacks](https://mlsanity.com/paper/2208.00428/) (2022)
- [Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation](https://mlsanity.com/paper/2005.01556/) (2020)

## Built on by (most cited first, 5 of 5)

- [Computational Approaches for Traditional Chinese Painting: From the "Six Principles of Painting" Perspective](https://mlsanity.com/paper/2307.14227/) (2023)
- [PoemTale Diffusion: Minimising Information Loss in Poem to Image Generation with Multi-Stage Prompt Refinement](https://mlsanity.com/paper/2507.13708/) (2025)
- [Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey](https://mlsanity.com/paper/2412.01450/) (2024)
- [ConCLVD: Controllable Chinese Landscape Video Generation via Diffusion Model](https://mlsanity.com/paper/2404.12903/) (2024)
- [Reviving Ancient Paintings via Poem: A Colorization Framework for Aligning Cultural Semantics](https://mlsanity.com/paper/2607.17638/) (2026)

## Abstract (arXiv)

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.