SplatBus: A Gaussian Splatting Viewer Framework via GPU Interprocess Communication
- URL: http://arxiv.org/abs/2601.15431v1
- Date: Wed, 21 Jan 2026 19:56:22 GMT
- Title: SplatBus: A Gaussian Splatting Viewer Framework via GPU Interprocess Communication
- Authors: Yinghan Xu, Théo Morales, John Dingliana,
- Abstract summary: Radiance field-based rendering methods have attracted significant interest from the computer vision and computer graphics communities.<n>They enable high-fidelity rendering with complex real-world lighting effects, but at the cost of high rendering time.<n>3D Splatting solves this issue with a Gaussianisation-based approach for real-time rendering.
- Score: 1.148281545083889
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Radiance field-based rendering methods have attracted significant interest from the computer vision and computer graphics communities. They enable high-fidelity rendering with complex real-world lighting effects, but at the cost of high rendering time. 3D Gaussian Splatting solves this issue with a rasterisation-based approach for real-time rendering, enabling applications such as autonomous driving, robotics, virtual reality, and extended reality. However, current 3DGS implementations are difficult to integrate into traditional mesh-based rendering pipelines, which is a common use case for interactive applications and artistic exploration. To address this limitation, this software solution uses Nvidia's interprocess communication (IPC) APIs to easily integrate into implementations and allow the results to be viewed in external clients such as Unity, Blender, Unreal Engine, and OpenGL viewers. The code is available at https://github.com/RockyXu66/splatbus.
Related papers
- Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform [104.39464309969253]
We present Visionary, an open, web-native platform for real-time various Gaussian Splatting and rendering.<n> Visionary enables dynamic neural processing while maintaining a lightweight, "click-to-run" browser experience.
arXiv Detail & Related papers (2025-12-09T10:54:58Z) - MeshSplatting: Differentiable Rendering with Opaque Meshes [59.240722437975755]
We present MeshSplatting, a mesh-based reconstruction approach that jointly optimize geometry and appearance through differentiable rendering.<n>On Mip-NeRF360, it boosts PSNR by +0.69 dB over the current state-of-the-art MiLo for mesh-based novel view synthesis.
arXiv Detail & Related papers (2025-12-07T12:31:04Z) - Triangle Splatting+: Differentiable Rendering with Opaque Triangles [54.18495204764292]
We introduce Triangle Splatting+, which directly optimize triangles within a differentiable splatting framework.<n>Our method surpasses prior splatting approaches in visual fidelity while remaining efficient and fast to training.<n>The resulting semi-connected meshes support downstream applications such as physics-based simulation or interactive walkthroughs.
arXiv Detail & Related papers (2025-09-29T17:43:46Z) - Blendify -- Python rendering framework for Blender [31.334130573156937]
Blendify is a Python-based framework that seamlessly integrates with Blender.
It automates object creation, handling the colors and material linking, and implementing features such as shadow-catcher objects.
arXiv Detail & Related papers (2024-10-23T13:29:02Z) - FIRE-3DV: Framework-Independent Rendering Engine for 3D Graphics using Vulkan [4.226502078427161]
This paper presents a performance-focused and lightweight rendering engine supporting the modern Vulkan graphics API.<n>Our engine is used to modernize the legacy rendering pipeline of the Asynchronous Multi-Body Framework (AMBF), a dynamic simulation framework.<n>Experiments show that the engine can render a simulated scene with over seven million triangles while maintaining GPU computation times within two milliseconds.
arXiv Detail & Related papers (2024-10-07T14:50:19Z) - EVER: Exact Volumetric Ellipsoid Rendering for Real-time View Synthesis [72.53316783628803]
We present Exact Volumetric Ellipsoid Rendering (EVER), a method for real-time differentiable emission-only volume rendering.<n>Unlike recentization based approach by 3D Gaussian Splatting (3DGS), our primitive based representation allows for exact volume rendering.<n>We show that our method is more accurate with blending issues than 3DGS and follow-up work on view rendering.
arXiv Detail & Related papers (2024-10-02T17:59:09Z) - 3D Gaussian Ray Tracing: Fast Tracing of Particle Scenes [50.36933474990516]
This work considers ray tracing the particles, building a bounding volume hierarchy and casting a ray for each pixel using high-performance ray tracing hardware.
To efficiently handle large numbers of semi-transparent particles, we describe a specialized algorithm which encapsulates particles with bounding meshes.
Experiments demonstrate the speed and accuracy of our approach, as well as several applications in computer graphics and vision.
arXiv Detail & Related papers (2024-07-09T17:59:30Z) - EvaSurf: Efficient View-Aware Implicit Textured Surface Reconstruction [53.28220984270622]
3D reconstruction methods should generate high-fidelity results with 3D consistency in real-time.<n>Our method can reconstruct high-quality appearance and accurate mesh on both synthetic and real-world datasets.<n>Our method can be trained in just 1-2 hours using a single GPU and run on mobile devices at over 40 FPS (Frames Per Second)
arXiv Detail & Related papers (2023-11-16T11:30:56Z) - Flexible Techniques for Differentiable Rendering with 3D Gaussians [29.602516169951556]
Neural Radiance Fields demonstrated photorealistic novel view is within reach, but was gated by performance requirements for fast reconstruction of real scenes and objects.
We develop extensions to alternative shape representations, in particular, 3D watertight meshes and rendering per-ray normals.
These reconstructions are quick, robust, and easily performed on GPU or CPU.
arXiv Detail & Related papers (2023-08-28T17:38:31Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.