AI & ML
GraftRay: Physically Based Mesh Insertion into Gaussian Splatting Scenes via Path Tracing
arXiv cs.GR0 views
arXiv:2610.37036v1 Announce Type: cross Abstract: Inserting virtual objects into scenes reconstructed via 2D or 3D Gaussian Splatting (2DGS/3DGS) is a key capability for content creation, AR, and synthetic data generation. However, realistic insertion requires the object to be seamlessly lit by the scene and, conversely, to cast physically plausible shadows onto it. Existing approaches either harmonize appearance in image space, sacrificing multi-view consistency, or approximate scene illumination with an environment map at the insertion point, which cannot represent near-field area lights such as windows and lamps that dominate indoor lighting. To address this, we present GraftRay, a unified method for physically consistent insertion of mesh objects into indoor scenes represented by either 2D or 3D Gaussians. We recover scene materials and surface normals with diffusion-based priors, and explicitly model spatially-extended emitters, solving their radiance in closed form. A hybrid renderer then jointly path-traces the scene Gaussians and inserted meshes, producing view-consistent shading, interreflections, and soft shadows. On FIPT, GraftRay sets a new state of the art, outperforming recent baselines such as ComGS and EAG-PT in rendering fidelity and shadow accuracy, while maintaining highly competitive rendering efficiency.
Source:https://arxiv.org/abs/2610.37036PreviousLingGS: Decoupling Feed-Forward Geometry Prediction from Camera Tracking for High-Fidelity Gaussian SLAMNextCTBakeGS: training-free baking of photorealistic CT volume renderings into 3D Gaussian splats
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