mlsanityData to 14 Oct 2026

SplatPainter: Interactive Authoring of 3D Gaussians from 2D Edits via Test-Time Training

arXiv 2512.05354 ↗First posted 5 Dec 2025cs.CV cs.GRcited by 7

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Abstract (arXiv)

The rise of 3D Gaussian Splatting has revolutionized photorealistic 3D asset creation, yet a critical gap remains for their interactive refinement and editing. Existing approaches based on diffusion or optimization are ill-suited for this task, as they are often prohibitively slow, destructive to the original asset's identity, or lack the precision for fine-grained control. To address this, we introduce SplatPainter, a state-aware feedforward model that enables continuous editing of 3D Gaussian assets from user-provided 2D view(s). Our method directly predicts updates to the attributes of a compact, feature-rich Gaussian representation and leverages Test-Time Training to create a state-aware, iterative workflow. The versatility of our approach allows a single architecture to perform diverse tasks, including high-fidelity local detail refinement, local paint-over, and consistent global recoloring, all at interactive speeds, paving the way for fluid and intuitive 3D content authoring.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 85 of its 106 references that are in the map. First posted on arXiv 5 Dec 2025.

Builds on

85 of 106 references.

References · 85

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38 more
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50 most cited of 85 All 85 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 7.

7 papers.