English

Diffusion-Based Visual Art Creation: A Survey and New Perspectives

Artificial Intelligence 2024-08-23 v1 Computer Vision and Pattern Recognition

Abstract

The integration of generative AI in visual art has revolutionized not only how visual content is created but also how AI interacts with and reflects the underlying domain knowledge. This survey explores the emerging realm of diffusion-based visual art creation, examining its development from both artistic and technical perspectives. We structure the survey into three phases, data feature and framework identification, detailed analyses using a structured coding process, and open-ended prospective outlooks. Our findings reveal how artistic requirements are transformed into technical challenges and highlight the design and application of diffusion-based methods within visual art creation. We also provide insights into future directions from technical and synergistic perspectives, suggesting that the confluence of generative AI and art has shifted the creative paradigm and opened up new possibilities. By summarizing the development and trends of this emerging interdisciplinary area, we aim to shed light on the mechanisms through which AI systems emulate and possibly, enhance human capacities in artistic perception and creativity.

Keywords

Cite

@article{arxiv.2408.12128,
  title  = {Diffusion-Based Visual Art Creation: A Survey and New Perspectives},
  author = {Bingyuan Wang and Qifeng Chen and Zeyu Wang},
  journal= {arXiv preprint arXiv:2408.12128},
  year   = {2024}
}

Comments

35 pages, 9 figures

R2 v1 2026-06-28T18:20:22.679Z