arXiv:2606.27584v1 Announce Type: cross Abstract: 3D scene inpainting is essential for reconstructing areas corrupted by occlusions or limited viewpoints. While recent methods leverage Gaussian Splatting (GS) for efficient 3D editing, they often depend on precise multi-view segmentation masks and are inherently constrained to object removal tasks. We propose CoIn, a novel framework that bridges 2D inpainting models and 3DGS through a multi-stage consistency pipeline. Our approach first generates initial inpainted images using a diffusion model, enabling the use of arbitrary-shaped masks and di
The rapid advancements in large diffusion models and 3D Gaussian Splatting are enabling novel approaches to complex 3D reconstruction and editing tasks.
This development significantly enhances foundational capabilities for 3D content creation, digital twins, and virtual environments, impacting sectors from entertainment to industrial design.
The ability to perform comprehensive 2D-3D inpainting with arbitrary masks and diffusion model guidance greatly expands the scope and quality of 3D scene reconstruction and editing beyond prior limitations.
- · 3D content creators
- · AI model developers
- · Gaming and VR/AR industries
- · Digital twin platforms
- · Manual 3D artists (for routine tasks)
- · Less efficient 3D reconstruction methods
- · Companies relying on limited 3D editing tools
More realistic and easily editable 3D environments become feasible for various applications.
The cost and time associated with generating high-quality 3D assets are reduced, democratizing access to complex 3D content creation.
This could accelerate the development of fully immersive metaverse applications and highly detailed simulations for engineering and urban planning.
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Read at arXiv cs.AI