Summary of Gooddrag: Towards Good Practices For Drag Editing with Diffusion Models, by Zewei Zhang et al.
GoodDrag: Towards Good Practices for Drag Editing with Diffusion Models
by Zewei Zhang, Huan Liu, Jun Chen, Xiangyu Xu
First submitted to arxiv on: 10 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Graphics (cs.GR); Machine Learning (cs.LG); Multimedia (cs.MM)
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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 paper introduces GoodDrag, a novel approach to improve the stability and image quality of drag editing. It presents an AlDD framework that alternates between drag and denoising operations within the diffusion process, enhancing the fidelity of the result. The authors also propose an information-preserving motion supervision operation to maintain the original features of the starting point for precise manipulation and artifact reduction. To evaluate GoodDrag, the paper contributes a new dataset, Drag100, and develops dedicated quality assessment metrics, Dragging Accuracy Index and Gemini Score, utilizing Large Multimodal Models. Extensive experiments demonstrate that GoodDrag compares favorably against state-of-the-art approaches both qualitatively and quantitatively. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary GoodDrag is a new way to make edited images look better. The problem with existing methods is that they can make the image look distorted or blurry if you edit it too much. GoodDrag fixes this by using an “alternating diffusion” process that combines editing and cleaning up the image. This helps keep the original features of the starting point while reducing artifacts. To test GoodDrag, the researchers created a new dataset called Drag100 and developed special metrics to measure how well it works. |
Keywords
» Artificial intelligence » Diffusion » Gemini
