Differentiable Surface Splatting for Point-based Geometry Processing
We propose Differentiable Surface Splatting (DSS), a high-fidelity differentiable renderer for point clouds. Gradients for point locations and normals are carefully designed to handle discontinuities of the rendering function. Regularization terms are introduced to ensure uniform distribution of the points on the underlying surface. We demonstrate applications of DSS to inverse rendering for geometry synthesis and denoising, where large scale topological changes, as well as small scale detail modifications, are accurately and robustly handled without requiring explicit connectivity, outperforming state-of-the-art techniques. The data and code are at https://github.com/yifita/DSS.
Code (1)
Tasks
DenoisingInverse RenderingSimilar Papers 제목 키워드 기반
GeoSplatting: Towards Geometry Guided Gaussian Splatting for Physically-based Inverse Rendering
We consider the problem of physically-based inverse rendering using 3D Gaussian Splatting (3DGS) representations. While recent 3DGS methods have achieved remarkable results in novel view synthesis (NVS), accurately captu…
3DGSDisentanglementInverse RenderingNovel View SynthesisPoint-Based 3D Reconstruction from Sparse Views under Known Illumination
Sparse view 3D reconstruction is commonly addressed with neural implicit surfaces or dense point-based representations such as Gaussian splatting. Surface-aware splatting methods improve extracted geometry through orient…
3D Reconstruction3DSS: 3D Surface Splatting for Inverse Rendering
We present 3D Surface Splatting (3DSS), the first differentiable surface splatting renderer for physically-based inverse rendering from multi-view images. Our central insight is that the surface separation problem at the…
Inverse RenderingMeshSplatting: Differentiable Rendering with Opaque Meshes
Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain incompatible with mesh-based pipelines tha…
Novel View SynthesisNeural Signed Distance Function Inference through Splatting 3D Gaussians Pulled on Zero-Level Set
It is vital to infer a signed distance function (SDF) in multi-view based surface reconstruction. 3D Gaussian splatting (3DGS) provides a novel perspective for volume rendering, and shows advantages in rendering efficien…
3DGSNeural RenderingSurface Reconstruction