Summary of Text Guided Image Editing with Automatic Concept Locating and Forgetting, by Jia Li et al.
Text Guided Image Editing with Automatic Concept Locating and Forgetting
by Jia Li, Lijie Hu, Zhixian He, Jingfeng Zhang, Tianhang Zheng, Di Wang
First submitted to arxiv on: 30 May 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 paper proposes a novel approach called Locate and Forget (LaF) for text-guided image editing, addressing the challenge of seamlessly incorporating objects into images based on textual instructions. LaF locates potential target concepts in the image by comparing syntactic trees between the target prompt and scene descriptions, intending to forget their existence clues in the generated image. Compared to baselines, LaF demonstrates superiority in both qualitative and quantitative text-guided image editing tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine being able to edit images based on written instructions. The paper introduces a new way to do this called Locate and Forget (LaF). LaF helps computers understand what objects are in an image and make changes to it based on what you want to happen. This approach is better than previous methods at making the desired changes, both visually and according to how well it does its job. |
Keywords
» Artificial intelligence » Prompt
