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SIGGRAPH Asia 2025 · 全部 301 篇
  • PartComposer: Learning and Composing Part-Level Concepts from Single-Image Examples
  • PartUV: Part-Based UV Unwrapping of 3D Meshes
  • Performance Analysis of Catch-Up Eye Movements in Visual Tracking
  • PhysHMR: Learning Humanoid Control Policies from Vision for Physically Plausible Human Motion Reconstruction
  • PhySIC: Physically Plausible 3D Human-Scene Interaction and Contact from a Single Image
  • ADD: Physics-Based Motion Imitation with Adversarial Differential Discriminators
  • PhysiOpt: Physics-Driven Shape Optimization for 3D Generative Models
  • PoissonNet: A Local-Global Approach for Learning on Surfaces
  • Potentially Visible Set Generation with the Disocclusion Buffer
  • PowerGS: Display-Rendering Power Co-Optimization for Neural Rendering in Power-Constrained XR Systems
  • Practical Gaussian Process Implicit Surfaces with Sparse Convolutions
  • PractiLight: Practical Light Control Using Foundational Diffusion Models
  • Precise Gradient Discontinuities in Neural Fields for Subspace Physics
  • Prior-Enhanced Gaussian Splatting for Dynamic Scene Reconstruction from Casual Video
  • PriorAvatar: Efficient and Robust Avatar Creation from Monocular Video Using Learned Priors
  • Procedural Scene Programs for Open-Universe Scene Generation: LLM-Free Error Correction via Program Search
  • Progressive Outfit Assembly and Instantaneous Pose Transfer
  • Proteus-ID: ID-Consistent and Motion-Coherent Video Customization
  • QMF-Blend: Quantized Matrix Factorization for Efficient Blendshape Compression
  • RaRa Clipper: A Clipper for Gaussian Splatting Based on Ray Tracer and Rasterizer
  • RCTrans: Transparent Object Reconstruction in Natural Scene via Refractive Correspondence Estimation
Journal

Practical Gaussian Process Implicit Surfaces with Sparse Convolutions

Kehan Xu, Benedikt Bitterli, Eugene d'Eon, Wojciech Jarosz

Dartmouth College; NVIDIA

SIGGRAPH Asia 2025RenderingGaussian Process Implicit SurfaceLight TransportRay TracingSparse ConvolutionRendering
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