Move and Act：面向图像编辑的增强型物体操控与背景完整性方法
Move and Act: Enhanced Object Manipulation and Background Integrity for Image Editing
AI总结：
针对现有三分支图像编辑方法对编辑物体位置控制不足、背景保留效果差的问题，提出无需微调的双分支一致性图像编辑方法，可同时编辑物体动作与位置并优化背景保留，经实验验证效果优异。
摘要：
当前方法通常采用反演、重建和编辑的三分支结构来解决一致性图像编辑任务，但这类方法缺乏对编辑后物体生成位置的控制，且存在背景保留效果不佳的问题。为克服这些局限，我们提出一种无需微调的双分支方法，仅包含反演和编辑两个分支。该方法允许用户同时编辑物体的动作并控制编辑后物体的生成位置，还能实现更优的背景保留效果。具体而言，我们在特定时间步的反演过程中，将编辑后的物体信息转移至目标区域，同时修复或保留其他区域的背景。在编辑阶段，我们利用自注意力中的图像特征查询反演过程中对应时间步的键和值，以实现一致性图像编辑。出色的图像编辑效果与定量评估结果证明了我们方法的有效性。代码可在https://github.com/mobiushy/move-act获取。
英文摘要：
Current methods commonly utilize three-branch structures of inversion, reconstruction, and editing, to tackle consistent image editing task. However, these methods lack control over the generation position of the edited object and have issues with background preservation. To overcome these limitations, we propose a tuning-free method with only two branches: inversion and editing. This approach allows users to simultaneously edit the object's action and control the generation position of the edited object. Additionally, it achieves improved background preservation. Specifically, we transfer the edited object information to the target area and repair or preserve the background of other areas during the inversion process at a specific time step. In the editing stage, we use the image features in self-attention to query the key and value of the corresponding time step in the inversion to achieve consistent image editing. Impressive image editing results and quantitative evaluation demonstrate the effectiveness of our method. The code is available at https://github.com/mobiushy/move-act.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
