SG-Splatting: Accelerating 3D Gaussian Splatting with Spherical Gaussians

• URL: http://arxiv.org/abs/2501.00342v1
• Date: Tue, 31 Dec 2024 08:31:52 GMT
• Title: SG-Splatting: Accelerating 3D Gaussian Splatting with Spherical Gaussians
• Authors: Yiwen Wang, Siyuan Chen, Ran Yi,
• Abstract summary: 3D Gaussian Splatting is emerging as a state-of-the-art technique in novel view synthesis. However, reliance on third-degree spherical harmonics for color representation introduces significant storage demands and computational overhead. We introduce SG-Splatting with Spherical Gaussians based color representation, a novel approach to enhance rendering speed and quality.
• Score: 21.00454010373162
• License:
• Abstract: 3D Gaussian Splatting is emerging as a state-of-the-art technique in novel view synthesis, recognized for its impressive balance between visual quality, speed, and rendering efficiency. However, reliance on third-degree spherical harmonics for color representation introduces significant storage demands and computational overhead, resulting in a large memory footprint and slower rendering speed. We introduce SG-Splatting with Spherical Gaussians based color representation, a novel approach to enhance rendering speed and quality in novel view synthesis. Our method first represents view-dependent color using Spherical Gaussians, instead of three degree spherical harmonics, which largely reduces the number of parameters used for color representation, and significantly accelerates the rendering process. We then develop an efficient strategy for organizing multiple Spherical Gaussians, optimizing their arrangement to achieve a balanced and accurate scene representation. To further improve rendering quality, we propose a mixed representation that combines Spherical Gaussians with low-degree spherical harmonics, capturing both high- and low-frequency color information effectively. SG-Splatting also has plug-and-play capability, allowing it to be easily integrated into existing systems. This approach improves computational efficiency and overall visual fidelity, making it a practical solution for real-time applications.

Related papers

• Deformable Beta Splatting [4.855751031707892]
  3D Gaussian Splatting (3DGS) has advanced radiance field reconstruction by enabling real-time rendering. We introduce Deformable Beta Splatting (DBS), a deformable and compact approach that enhances both geometry and color representation.
  arXiv  Detail & Related papers  (2025-01-27T18:58:43Z)
• SpecGaussian with Latent Features: A High-quality Modeling of the View-dependent Appearance for 3D Gaussian Splatting [11.978842116007563]
  Lantent-SpecGS is an approach that utilizes a universal latent neural descriptor within each 3D Gaussian. Two parallel CNNs are designed to decoder the splatting feature maps into diffuse color and specular color separately. A mask that depends on the viewpoint is learned to merge these two colors, resulting in the final rendered image.
  arXiv  Detail & Related papers  (2024-08-23T15:25:08Z)
• Compact 3D Gaussian Splatting for Static and Dynamic Radiance Fields [13.729716867839509]
  We propose a learnable mask strategy that significantly reduces the number of Gaussians while preserving high performance. In addition, we propose a compact but effective representation of view-dependent color by employing a grid-based neural field. Our work provides a comprehensive framework for 3D scene representation, achieving high performance, fast training, compactness, and real-time rendering.
  arXiv  Detail & Related papers  (2024-08-07T14:56:34Z)
• Splatfacto-W: A Nerfstudio Implementation of Gaussian Splatting for Unconstrained Photo Collections [25.154665328053333]
  We introduce Splatfacto-W, an in-trivial approach that integrates per-Gaussian neural color features and per-image appearance embeddings into an rendering process. Our method improves the Peak Signal-to-Noise Ratio (PSNR) by an average of 5.3 dB compared to 3DGS, enhances training speed by 150 times compared to NeRF-based methods, and achieves a similar rendering speed to 3DGS.
  arXiv  Detail & Related papers  (2024-07-17T04:02:54Z)
• MVSGaussian: Fast Generalizable Gaussian Splatting Reconstruction from Multi-View Stereo [54.00987996368157]
  We present MVSGaussian, a new generalizable 3D Gaussian representation approach derived from Multi-View Stereo (MVS) MVSGaussian achieves real-time rendering with better synthesis quality for each scene.
  arXiv  Detail & Related papers  (2024-05-20T17:59:30Z)
• RTG-SLAM: Real-time 3D Reconstruction at Scale using Gaussian Splatting [51.51310922527121]
  We present a real-time 3D reconstruction system with an RGBD camera for large-scale environments using Gaussian splatting. We force each Gaussian to be either opaque or nearly transparent, with the opaque ones fitting the surface and dominant colors, and transparent ones fitting residual colors. We show real-time reconstructions of a variety of large scenes and show superior performance in the realism of novel view synthesis and camera tracking accuracy.
  arXiv  Detail & Related papers  (2024-04-30T16:54:59Z)
• HO-Gaussian: Hybrid Optimization of 3D Gaussian Splatting for Urban Scenes [24.227745405760697]
  We propose a hybrid optimization method named HO-Gaussian, which combines a grid-based volume with the 3DGS pipeline. Results on widely used autonomous driving datasets demonstrate that HO-Gaussian achieves photo-realistic rendering in real-time on multi-camera urban datasets.
  arXiv  Detail & Related papers  (2024-03-29T07:58:21Z)
• GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering [112.16239342037714]
  GES (Generalized Exponential Splatting) is a novel representation that employs Generalized Exponential Function (GEF) to model 3D scenes. With the aid of a frequency-modulated loss, GES achieves competitive performance in novel-view synthesis benchmarks.
  arXiv  Detail & Related papers  (2024-02-15T17:32:50Z)
• Scaffold-GS: Structured 3D Gaussians for View-Adaptive Rendering [71.44349029439944]
  Recent 3D Gaussian Splatting method has achieved the state-of-the-art rendering quality and speed. We introduce Scaffold-GS, which uses anchor points to distribute local 3D Gaussians. We show that our method effectively reduces redundant Gaussians while delivering high-quality rendering.
  arXiv  Detail & Related papers  (2023-11-30T17:58:57Z)
• GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting [51.96353586773191]
  We introduce textbfGS-SLAM that first utilizes 3D Gaussian representation in the Simultaneous Localization and Mapping system. Our method utilizes a real-time differentiable splatting rendering pipeline that offers significant speedup to map optimization and RGB-D rendering. Our method achieves competitive performance compared with existing state-of-the-art real-time methods on the Replica, TUM-RGBD datasets.
  arXiv  Detail & Related papers  (2023-11-20T12:08:23Z)
• NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAM [111.83168930989503]
  NICER-SLAM is a dense RGB SLAM system that simultaneously optimize for camera poses and a hierarchical neural implicit map representation. We show strong performance in dense mapping, tracking, and novel view synthesis, even competitive with recent RGB-D SLAM systems.
  arXiv  Detail & Related papers  (2023-02-07T17:06:34Z)

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.