mlsanityData to 14 Oct 2026

End-to-End Chinese Landscape Painting Creation Using Generative Adversarial Networks

arXiv 2011.05552 ↗First posted 11 Nov 2020cs.CV cs.LG eess.IVcited by 18

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Abstract (arXiv)

Current GAN-based art generation methods produce unoriginal artwork due to their dependence on conditional input. Here, we propose Sketch-And-Paint GAN (SAPGAN), the first model which generates Chinese landscape paintings from end to end, without conditional input. SAPGAN is composed of two GANs: SketchGAN for generation of edge maps, and PaintGAN for subsequent edge-to-painting translation. Our model is trained on a new dataset of traditional Chinese landscape paintings never before used for generative research. A 242-person Visual Turing Test study reveals that SAPGAN paintings are mistaken as human artwork with 55% frequency, significantly outperforming paintings from baseline GANs. Our work lays a groundwork for truly machine-original art generation.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Nov 2020.

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Citing papers per year: 2021: 3; 2022: 1; 2023: 4; 2024: 8; 2025: 2.

18 papers.

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  1. 2022The ArtBench Dataset: Benchmarking Generative Models with Artworkscited by 64
  2. 2021Weather GAN: Multi-Domain Weather Translation Using Generative Adversarial Networkscited by 18
  3. 2025QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generationcited by 9
  4. 2023CCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Modelcited by 5
  5. 2023Learning to Generate Poetic Chinese Landscape Painting with Calligraphycited by 5
  6. 2025SCSA: A Plug-and-Play Semantic Continuous-Sparse Attention for Arbitrary Semantic Style Transfercited by 4
  7. 2023Computational Approaches for Traditional Chinese Painting: From the "Six Principles of Painting" Perspectivecited by 3
  8. 2023Controllable Multi-domain Semantic Artwork Synthesiscited by 2
  9. 2024SRAGAN: Saliency Regularized and Attended Generative Adversarial Network for Chinese Ink-wash Painting Style Transfercited by 2
  10. 2021Continuation of Famous Art with AI: A Conditional Adversarial Network Inpainting Approachcited by 1
  11. 2024Artistic Intelligence: A Diffusion-Based Framework for High-Fidelity Landscape Painting Synthesiscited by 1
  12. 2024Semi-supervised Chinese Poem-to-Painting Generation via Cycle-consistent Adversarial Networkscited by 1
6 more
  1. 2024Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Surveycited by 1
  2. 2021The Work of Art in an Age of Mechanical Generationcited by 0
  3. 2024Scene Depth Estimation from Traditional Oriental Landscape Paintingscited by 0
  4. 2024DLP-GAN: learning to draw modern Chinese landscape photos with generative adversarial networkcited by 0
  5. 2024ConCLVD: Controllable Chinese Landscape Video Generation via Diffusion Modelcited by 0
  6. 2024Neural-Polyptych: Content Controllable Painting Recreation for Diverse Genrescited by 0