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.
Retinags: Scalable training for dense scene ren- dering with billion-scale 3d gaussians.arXiv preprint arXiv:2406.11836
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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.
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.