AI RESEARCH
3DEditSafe: Defending 3D Editing Pipelines from Unsafe Generation
arXiv CS.CV
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ArXi:2605.15398v1 Announce Type: cross Recent advances in 3D generative editing, particularly pipelines based on 3D Gaussian Splatting (3DGS), have achieved high-fidelity, multi-view-consistent scene manipulation from text prompts. However, we find that these pipelines also To address this, we propose 3DEditSafe, a safety-regularized 3D editing framework that constrains unsafe semantic propagation during optimization.