Summary of Diffusion-based Visual Art Creation: a Survey and New Perspectives, by Bingyuan Wang et al.
Diffusion-Based Visual Art Creation: A Survey and New Perspectives
by Bingyuan Wang, Qifeng Chen, Zeyu Wang
First submitted to arxiv on: 22 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The survey explores the integration of generative AI in visual art, examining its development from both artistic and technical perspectives. It structures the survey into three phases: data feature and framework identification, detailed analyses using a structured coding process, and open-ended prospective outlooks. The findings reveal how artistic requirements are transformed into technical challenges and highlight the design and application of diffusion-based methods within visual art creation. The study suggests that the confluence of generative AI and art has shifted the creative paradigm and opened up new possibilities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The survey looks at how artificial intelligence (AI) is used to create new kinds of art. It talks about three stages: understanding what makes good art, analyzing how AI helps with this process, and looking forward to what might happen in the future. The study finds that using AI to make art is a two-way street – it changes how we approach making art, and also shows us new ways to use AI. This has changed how we think about creativity and opens up new possibilities. |
Keywords
» Artificial intelligence » Diffusion
