title: CompGS: Efficient 3D Scene Representation via Compressed Gaussian
    Splatting
summary: Gaussian splatting, renowned for its exceptional rendering quality and
  efficiency, has emerged as a prominent technique in 3D scene representation.
  However, the substantial data volume of Gaussian splatting impedes its
  practical utility in real-world applications. Herein, we propose an efficient
  3D scene representation, named Compressed Gaussian Splatting (CompGS), which
  harnesses compact Gaussian primitives for faithful 3D scene modeling with a
  remarkably reduced data size. To ensure the compactness of Gaussian primitives,
  we devise a hybrid primitive structure that captures predictive relationships
  between each other. Then, we exploit a small set of anchor primitives for
  prediction, allowing the majority of primitives to be encapsulated into highly
  compact residual forms. Moreover, we develop a rate-constrained optimization
  scheme to eliminate redundancies within such hybrid primitives, steering our
  CompGS towards an optimal trade-off between bitrate consumption and
  representation efficacy. Experimental results show that the proposed CompGS
  significantly outperforms existing methods, achieving superior compactness in
  3D scene representation without compromising model accuracy and rendering
  quality. Our code will be released on GitHub for further research.
paper_authors._id: 661df97c5d2a38b1dc5a1bf1
paper_authors.name: Xiangrui Liu
paper_authors._id: 661df97c5d2a38b1dc5a1bf2
paper_authors.name: Xinju Wu
paper_authors._id: 661df97c5d2a38b1dc5a1bf3
paper_authors.name: Pingping Zhang
paper_authors._id: 661df97c5d2a38b1dc5a1bf4
paper_authors.name: Shiqi Wang
paper_authors._id: 661df97c5d2a38b1dc5a1bf5
paper_authors.name: Zhu Li
paper_authors._id: 661df97c5d2a38b1dc5a1bf6
paper_authors.name: Sam Kwong
paper_title: CompGS: Efficient 3D Scene Representation via Compressed Gaussian
    Splatting
paper_summary: Gaussian splatting, renowned for its exceptional rendering quality and
  efficiency, has emerged as a prominent technique in 3D scene representation.
  However, the substantial data volume of Gaussian splatting impedes its
  practical utility in real-world applications. Herein, we propose an efficient
  3D scene representation, named Compressed Gaussian Splatting (CompGS), which
  harnesses compact Gaussian primitives for faithful 3D scene modeling with a
  remarkably reduced data size. To ensure the compactness of Gaussian primitives,
  we devise a hybrid primitive structure that captures predictive relationships
  between each other. Then, we exploit a small set of anchor primitives for
  prediction, allowing the majority of primitives to be encapsulated into highly
  compact residual forms. Moreover, we develop a rate-constrained optimization
  scheme to eliminate redundancies within such hybrid primitives, steering our
  CompGS towards an optimal trade-off between bitrate consumption and
  representation efficacy. Experimental results show that the proposed CompGS
  significantly outperforms existing methods, achieving superior compactness in
  3D scene representation without compromising model accuracy and rendering
  quality. Our code will be released on GitHub for further research.
paper_ai_keywords: Gaussian splatting rendering quality efficiency 3D scene representation data volume Compressed Gaussian Splatting (CompGS) Gaussian primitives 3D scene modeling hybrid primitive structure predictive relationships anchor primitives residual forms rate-constrained optimization bitrate consumption representation efficacy compactness