Summary of Towards Efficient Diffusion-based Image Editing with Instant Attention Masks, by Siyu Zou et al.
Towards Efficient Diffusion-Based Image Editing with Instant Attention Masks
by Siyu Zou, Jiji Tang, Yiyi Zhou, Jing He, Chaoyi Zhao, Rongsheng Zhang, Zhipeng Hu, Xiaoshuai Sun
First submitted to arxiv on: 15 Jan 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 paper proposes Instant Diffusion Editing (InstDiffEdit), a novel method for text-to-image diffusion models that enables instant mask guidance during the diffusion steps. InstDiffEdit utilizes cross-modal attention abilities to achieve automatic and accurate mask generation, reducing noise through a training-free refinement scheme. The authors also introduce a new benchmark, Editing-Mask, to evaluate mask accuracy and local editing ability of existing methods. Experimental results on ImageNet and Imagen show that InstDiffEdit outperforms SOTA methods in image quality and editing results while having a significantly faster inference speed (+5-6 times). This research contributes to the growing field of diffusion-based image editing (DIE) by providing an efficient solution for text-to-image diffusion models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to edit images using computer models. Usually, these models need help deciding what parts of the image to change. The authors came up with a clever idea called Instant Diffusion Editing that lets the model figure it out on its own, just by looking at the text description of what you want to see in the image. They also created a new way to test how well different methods work at editing images. When they tried their method out, it worked better than other popular methods and was much faster too! This is an important step forward for people who want to use computer models to edit and create new images. |
Keywords
* Artificial intelligence * Attention * Diffusion * Inference * Mask
