Summary of Fill in the ____ (a Diffusion-based Image Inpainting Pipeline), by Eyoel Gebre et al.
Fill in the ____ (a Diffusion-based Image Inpainting Pipeline)
by Eyoel Gebre, Krishna Saxena, Timothy Tran
First submitted to arxiv on: 24 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper provides an overview of the progress in image inpainting techniques, highlighting their strengths and weaknesses. The authors identify a critical gap in existing models, focusing on the ability to prompt and control what is generated. They argue that this is the next logical step for inpainting models and propose multiple approaches to achieving this functionality. The results are evaluated qualitatively, with an emphasis on generating high-quality images that correctly inpaint regions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Inpainting is a technique used to fill in gaps or remove unwanted parts from images. This technology has many uses, including restoring old pictures, improving image quality after compression, and removing objects/text from images. Current inpainting methods are good at filling in gaps, but there’s still room for improvement. The authors of this paper will discuss the current state of inpainting techniques, what works well, and what doesn’t. They’ll also propose new ways to control what is generated and show examples of how these new approaches work. |
Keywords
» Artificial intelligence » Image inpainting » Prompt
