HiGS achieves up to 15.8x faster real-time 3D Gaussian Splatting by running partitioning at coarse macro-tile scale and rasterization at fine tile scale, issuing work proportional to Gaussians per macro-tile.
Balanced 3dgs: Gaussian-wise parallelism rendering with fine-grained tiling.arXiv preprint arXiv:2412.17378
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
TideGS scales 3D Gaussian Splatting to over one billion primitives on a single 24 GB GPU by using block-virtualized geometry, asynchronous I/O pipelines, and trajectory-adaptive differential streaming to exploit training sparsity.
SparseOIT uses active set optimization on sparse dependencies from OIT-modified 3DGS rendering equations to improve reconstruction speed and quality for transparent materials.
citing papers explorer
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HiGS: A Hierarchical Rendering Architecture for Real-Time 3D Gaussian Splatting
HiGS achieves up to 15.8x faster real-time 3D Gaussian Splatting by running partitioning at coarse macro-tile scale and rasterization at fine tile scale, issuing work proportional to Gaussians per macro-tile.
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TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization
TideGS scales 3D Gaussian Splatting to over one billion primitives on a single 24 GB GPU by using block-virtualized geometry, asynchronous I/O pipelines, and trajectory-adaptive differential streaming to exploit training sparsity.
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SparseOIT: Improving Order-Independent Transparency 3DGS via Active Set Method
SparseOIT uses active set optimization on sparse dependencies from OIT-modified 3DGS rendering equations to improve reconstruction speed and quality for transparent materials.