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...
Yang Luo, Yan Gong, Yongsheng Gao et al.· 0 citations
Novel view synthesis is a key task for dynamic scene reconstruction, where high rendering speed is essential for applications such as virtual reality. Existing deformable Gaussian Splatting methods achieve high-fidelity dynamic scene modeling, but still face limitations in memory usage and rendering efficiency due to t...
Hui-Wen Xue, Kai-Xing Zhao, Zuheng Ming et al.· 0 citations
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.
Zhenyu Xia, Pengcheng Han, Lin Chen et al.· IEEE Transactions on Visuali...· 0 citations
3D Gaussian splatting (3DGS) has drawn significant attention in the architectural community recently. However, enabling city scale 3DGS on mobile VR devices remains challenging, as the memory requirement of large scale scenes far exceeds the memory capacity of today's mobile GPUs. This paper presents Atlas, an on devic...
He Zhu, Zheng Liu, Xingyang Li et al.· 0 citations
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...
Seung-Eon Hwang, Jongsun Park· International Symposium on L...· 0 citations
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...
Hanjun Choi, Hyerin Lim, Joongho Jo et al.· International Symposium on L...· 0 citations
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