拖拽与几何：从像素到几何引导的图像编辑
Dragging with Geometry: From Pixels to Geometry-Guided Image Editing
AI总结：
GeoDrag通过整合3D几何线索和统一位移场，实现了高精度、结构一致的拖拽图像编辑，解决了多点拖拽冲突和几何引导不连续性问题。
摘要：
交互式基于点的图像编辑作为一种可控的编辑器，能够实现对图像内容的精确和灵活的操控。然而，大多数拖拽方法主要在2D像素平面上操作，对3D线索的利用有限。因此，它们常常产生不精确且不一致的编辑效果，特别是在几何密集的场景中，如旋转和透视变换。为了解决这些限制，我们提出了一种新的几何引导的拖拽图像编辑方法GeoDrag，以解决三个关键挑战：1）将3D几何线索融入像素级编辑；2）减轻由几何引导引起的不连续性；3）解决多点拖拽产生的冲突。基于一个统一的位移场，该场联合编码了3D几何和2D空间先验，GeoDrag能够在单次前向传递中实现一致、高保真和结构一致的编辑。此外，引入了一种无冲突的分区策略，以隔离编辑区域，有效防止干扰并确保一致性。在各种编辑场景中的广泛实验验证了我们方法的有效性，显示出优越的精度、结构一致性和可靠的多点编辑能力。项目页面：https://xinyu-pu.github.io/projects/geodrag。
英文摘要：
Interactive point-based image editing serves as a controllable editor, enabling precise and flexible manipulation of image content. However, most drag-based methods operate primarily on the 2D pixel plane with limited use of 3D cues. As a result, they often produce imprecise and inconsistent edits, particularly in geometry-intensive scenarios such as rotations and perspective transformations. To address these limitations, we propose a novel geometry-guided drag-based image editing method-GeoDrag, which addresses three key challenges: 1) incorporating 3D geometric cues into pixel-level editing, 2) mitigating discontinuities caused by geometry-only guidance, and 3) resolving conflicts arising from multi-point dragging. Built upon a unified displacement field that jointly encodes 3D geometry and 2D spatial priors, GeoDrag enables coherent, high-fidelity, and structure-consistent editing in a single forward pass. In addition, a conflict-free partitioning strategy is introduced to isolate editing regions, effectively preventing interference and ensuring consistency. Extensive experiments across various editing scenarios validate the effectiveness of our method, showing superior precision, structural consistency, and reliable multi-point editability. Project page: https://xinyu-pu.github.io/projects/geodrag.
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。
