Summary of Brushedit: All-in-one Image Inpainting and Editing, by Yaowei Li et al.
BrushEdit: All-In-One Image Inpainting and Editing
by Yaowei Li, Yuxuan Bian, Xuan Ju, Zhaoyang Zhang, Ying Shan, Yuexian Zou, Qiang Xu
First submitted to arxiv on: 13 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 This research paper proposes a novel image editing paradigm called BrushEdit, which leverages multimodal large language models (MLLMs) and image inpainting models to enable interactive free-form instruction editing. The proposed framework integrates MLLMs and a dual-branch image inpainting model in an agent-cooperative framework to perform editing category classification, main object identification, mask acquisition, and editing area inpainting. The paper demonstrates the effectiveness of this framework across seven metrics, including mask region preservation and editing effect coherence. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine being able to easily edit images by giving instructions like “add a cat” or “remove the background”. That’s what this research is all about! They’re trying to make it easier for people to edit images without having to be experts. Right now, there are two main ways to do image editing: either by using special algorithms that can change parts of an image (but don’t work well for big changes), or by giving instructions to a computer program (but it’s hard to control exactly what happens). This new approach combines the best of both worlds and lets users give instructions and see the results in real-time. The researchers tested their method on many different images and found that it worked really well, making sure the edited areas looked natural and consistent. |
Keywords
» Artificial intelligence » Classification » Image inpainting » Mask
