arXiv 2608.031792026-08-05cs.CV

EditFlow3D：保留轨迹的3D资产自动化局部编辑

EditFlow3D: Automated Local Editing of 3D Assets with Trajectory Preservation

Rui Nie, Chuang Wang, Haitao Zhou, Jiahe Song, Buyu Li, Sheng Wang, Qian Yu

AI总结：

EditFlow3D是一种无需训练的3D局部编辑框架，通过VLM驱动工作流生成掩码与视觉引导，结合掩码引导差分流和轨迹保留技术，在新基准EditFlow-Bench上验证了其编辑准确性与非目标区域保留能力优于现有方法。

AI中文摘要：

3D资产的可控局部编辑需要精确的目标定位和合适的视觉引导。然而，现有方法缺乏一种简单且准确的方式来获取3D掩码，且难以在忠实保留非目标区域结构与外观的同时实现预期编辑。为应对这些挑战，我们提出EditFlow3D，这是一种无需训练的局部3D编辑框架。给定源资产和编辑指令，一个VLM驱动的工作流会解析编辑意图，并自动构建视觉引导图像和优化后的3D编辑掩码，从而在预训练3D生成模型的原生表示空间中实现局部编辑。具体而言，掩码引导的差分流将编辑聚焦于目标区域，而逐步轨迹保留则在不直接替换中间特征的情况下，维持非目标区域与源资产之间的一致性。由于现有Edit3D-Bench仅覆盖有限的局部编辑类别，我们进一步引入EditFlow-Bench作为补充基准，涵盖更广泛的结构和外观编辑，并在两个基准上对EditFlow3D进行评估。定量结果、定性比较和用户研究表明，与现有3D编辑方法相比，EditFlow3D实现了更准确的目标区域编辑，并更好地保留了非目标区域。

英文摘要：

Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple yet accurate way to obtain 3D masks and struggle to achieve the desired edit while faithfully preserving the structure and appearance of non-target regions. To address these challenges, we present EditFlow3D, a training-free framework for local 3D editing. Given a source asset and an edit instruction, a VLM-driven workflow interprets the editing intent and automatically constructs a visual guidance image and a refined 3D editing mask, enabling localized editing in the native representation space of a pretrained 3D generative model. Specifically, mask-guided differential flow focuses the edit on the target region, while step-wise trajectory preservation maintains consistency between non-target regions and the source asset without directly replacing intermediate features. Since the existing Edit3D-Bench covers only a limited range of local editing categories, we further introduce EditFlow-Bench as a complementary benchmark encompassing a broader variety of structural and appearance edits, and evaluate EditFlow3D on both benchmarks. Quantitative results, qualitative comparisons, and a user study demonstrate that EditFlow3D achieves more accurate target-region editing and better preserves non-target regions than existing 3D editing methods.