MrNeRF (@janusch_patas)
2026-02-04 | โค๏ธ 42 | ๐ 9 | ๐ฌ 2
WebSplatter: Enabling Cross-Device Efficient Gaussian Splatting in Web Browsers via WebGPU
Contributions: โข An end-to-end WebGPU framework for 3D Gaussian Splatting. We present WebSplatter, the first framework that bridges the gap between native GPU capabilities and the sandboxed web environment. Unlike direct ports of native algorithms, which fail due to the lack of low-level thread interlocks in browsers, WebSplatter employs a wait-free, multi-stage parallel pipeline designed specifically to guarantee synchronization and deadlock-free execution on the Web.
โข Optimization for cross-platform WebGPU backends. We propose a set of techniques that ensure stable and efficient performance across diverse devices. A wait-free radix sort eliminates inter-workgroup spin waiting and guarantees deadlock-free execution on GPUs from different vendors. Screen-space culling and opacity-driven quad sizing further reduce the overall computational workload and improve runtime efficiency.
โข Comprehensive Evaluation on Performance. We evaluate WebSplatter across diverse hardware platforms. The framework achieves speedups ranging from 1.18ร to 4.5ร over state-of-the-art baselines. Furthermore, we demonstrate that WebSplatter reduces peak memory consumption compared to existing WebGPU ports, preventing crashes on memory-constrained devices.
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