Summary of Surrealistic-like Image Generation with Vision-language Models, by Elif Ayten et al.
Surrealistic-like Image Generation with Vision-Language Models
by Elif Ayten, Shuai Wang, Hjalmar Snoep
First submitted to arxiv on: 18 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 proposed study investigates the use of vision-language generative models to create images inspired by surrealist paintings. The authors examine the performance of various models, including DALL-E, Deep Dream Generator, and DreamStudio, under different image generation settings. Their primary goal is to determine the most suitable model and settings for generating surrealistic images. Additionally, they explore the impact of using edited base images on the resulting generated images. Through their experiments, they evaluate the performance of selected models and gain insights into their capabilities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The study uses artificial intelligence to create pictures that look like famous surrealist paintings. The researchers tested different AI models to see which one works best for making these types of images. They wanted to know what settings to use to get the best results and if using edited base images makes a difference. By doing this, they can tell us which model is most useful for creating surrealistic images. |
Keywords
» Artificial intelligence » Image generation
