用文本提示精准编辑图片，保持原图又生成新内容。
SeedEdit: Align Image Re-Generation to Image Editing
- 从弱生成器逐步优化，平衡图像重建与重生成。
- 支持对扩散模型生成图的多次连续编辑，效果更稳定多样。
- 适合需要精细控制图像修改的研究者和设计师。
我们提出SeedEdit，一种能够根据任意文本提示修改给定图像的扩散模型。我们认为该任务的关键在于在保持原图（图像重建）和生成新图（图像重生成）之间取得最佳平衡。为此，我们从一个弱生成器（文本到图像模型）出发，生成两类方向的多样化样本，并逐步将其调整为强图像编辑器，能良好平衡两项任务。相比以往图像编辑方法，SeedEdit具备更强的多样性与稳定性，可对扩散模型生成的图像进行连续修改。
原文摘要 · Abstract (English)
We introduce SeedEdit, a diffusion model that is able to revise a given image with any text prompt. In our perspective, the key to such a task is to obtain an optimal balance between maintaining the original image, i.e. image reconstruction, and generating a new image, i.e. image re-generation. To this end, we start from a weak generator (text-to-image model) that creates diverse pairs between such two directions and gradually align it into a strong image editor that well balances between the two tasks. SeedEdit can achieve more diverse and stable editing capability over prior image editing methods, enabling sequential revision over images generated by diffusion models.
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