Jul 2026· International Conference on Computer Graphics and Interactive Techniques· pp. 1-11· 0 citations· 87 references
Computer Science
TL;DR
SHARP-GS is a high-performance framework that unlocks real-time 8K rendering for immersive virtual experiences by overcoming the scaling bottlenecks of 3D Gaussian Splatting by overcoming the scaling bottlenecks of 3D Gaussian Splatting.
Abstract
We present SHARP-GS, a high-performance framework that unlocks real-time 8K rendering for immersive virtual experiences by overcoming the scaling bottlenecks of 3D Gaussian Splatting (3DGS). While 3DGS excels at real-time view synthesis, its performance degrades non-linearly at ultra-high resolutions due to excessive binning overhead, uncoalesced memory access, and redundant per-pixel arithmetic. SHARP-GS addresses these inefficiencies through three key contributions: (i) Resolution-Aware Adaptive Binning, which maintains a constant overlap factor via dynamic tile sizing and employs fine-grained sub-tile culling; (ii) a Morton-Ordered Memory Layout to ensure spatially coherent memory access; and (iii) Forward Differencing, which replaces expensive probability density function evaluations with efficient incremental updates. On high-end consumer GPUs, our framework achieves an average 2.55× speedup at 8K resolution, sustaining over 250 FPS with negligible visual quality loss. This performance delivers the necessary pixel throughput to enable high-fidelity, 120 Hz stereoscopic VR experiences. Code and data for this paper are at https://github.com/dingjr7/SHARP-GS.
3D Gaussian Splatting (3DGS) enables real-time novel-view synthesis but remains limited on GPUs at high resolutions. Through a stage-wise Roofline characterization, we identify two distinct hardware bottlenecks: global memory traffic dominates the front end, whereas instruction throughput limits rasterization. Guided b...
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InfoLoD introduces a Fisher-guided self-distillation scheme that uses the Fisher Information Matrix to select geometrically valid, information-rich pseudo viewpoints, enabling LoD training directly from a pre-trained 3DGS model without any original images.
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Atlas is presented, an on device city scale 3DGS rendering framework that enables scalable rendering without runtime Internet access and proposes temporal aware LoD search and stereo rasterization to avoid redundant computation in VR.
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3D-Gaussian Splatting (3D-GS) enables high-quality novel view synthesis for virtual reality (VR) and augmented reality (AR) applications. Recently, Scaffold-GS is proposed to further improve rendering visual quality by generating view-conditioned Gaussians with voxel-level multi-layer perceptrons (MLPs). However, voxel...
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Classical image compression techniques exploit the importance differences existing between low-frequency and high-frequency of image data. In 3D Gaussian Splatting (3D-GS), pruning approaches have been widely employed to reduce computational complexity, but those are applied to uniform criteria without considering freq...
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