mlsanityData to 14 Oct 2026

3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing

arXiv 2601.07963 ↗First posted 12 Jan 2026cs.CVcited by 4

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Abstract (arXiv)

The transformative potential of 3D content creation has been progressively unlocked through advancements in generative models. Recently, intuitive drag editing with geometric changes has attracted significant attention in 2D editing yet remains challenging for 3D scenes. In this paper, we introduce 3DGS-Drag -- a point-based 3D editing framework that provides efficient, intuitive drag manipulation of real 3D scenes. Our approach bridges the gap between deformation-based and 2D-editing-based 3D editing methods, addressing their limitations to geometry-related content editing. We leverage two key innovations: deformation guidance utilizing 3D Gaussian Splatting for consistent geometric modifications and diffusion guidance for content correction and visual quality enhancement. A progressive editing strategy further supports aggressive 3D drag edits. Our method enables a wide range of edits, including motion change, shape adjustment, inpainting, and content extension. Experimental results demonstrate the effectiveness of 3DGS-Drag in various scenes, achieving state-of-the-art performance in geometry-related 3D content editing. Notably, the editing is efficient, taking 10 to 20 minutes on a single RTX 4090 GPU.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 43 of its 51 references that are in the map. First posted on arXiv 12 Jan 2026.

Builds on

43 of 51 references.

References · 43

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31 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026DAV-GSWT: Diffusion-Active-View Sampling for Data-Efficient Gaussian Splatting Wang Tilescited by 2
  2. 2026AdvSplat: Adversarial Attacks on Feed-Forward Gaussian Splatting Modelscited by 0
  3. 2026AdaptiveSplat:Texture Aware Controllable 3D Gaussian Allocation for Feed-Forward Reconstructioncited by 0
  4. 2026NormLift: From Lifted Features To Semantic Reliability In 3D Gaussian Splattingcited by 0