paper-with-me

Papers

GSCodec Studio: A Modular Framework for Gaussian Splat Compression

2025-06-02 · Sicheng Li, Chengzhen Wu, Hao Li, Xiang Gao, Yiyi Liao, Lu Yu

3D Gaussian Splatting and its extension to 4D dynamic scenes enable photorealistic, real-time rendering from real-world captures, positioning Gaussian Splats (GS) as a promising format for next-generation immersive media. However, their high storage requirements pose significant challenges for practical use in sharing, transmission, and storage. Despite various studies exploring GS compression from different perspectives, these efforts remain scattered across separate repositories, complicating benchmarking and the integration of best practices. To address this gap, we present GSCodec Studio, a unified and modular framework for GS reconstruction, compression, and rendering. The framework incorporates a diverse set of 3D/4D GS reconstruction methods and GS compression techniques as modular components, facilitating flexible combinations and comprehensive comparisons. By integrating best practices from community research and our own explorations, GSCodec Studio supports the development of compact representation and compression solutions for static and dynamic Gaussian Splats, namely our Static and Dynamic GSCodec, achieving competitive rate-distortion performance in static and dynamic GS compression. The code for our framework is publicly available at https://github.com/JasonLSC/GSCodec_Studio , to advance the research on Gaussian Splats compression.

📄 PDF Abstract BibTeX arXiv:2506.01822

Code (1)

jasonlsc/gscodec_studio 공식 구현 pytorch

Tasks

Benchmarking

Methods 이 논문이 사용한 방법론

SET Dynamic Sparse Training method where weight mask is updated randomly periodically

Similar Papers 제목 키워드 기반

GauStudio: A Modular Framework for 3D Gaussian Splatting and Beyond

2024-03-28 · Chongjie Ye, Yinyu Nie, Jiahao Chang, Yuantao Chen 외

We present GauStudio, a novel modular framework for modeling 3D Gaussian Splatting (3DGS) to provide standardized, plug-and-play components for users to easily customize and implement a 3DGS pipeline. Supported by our fr…

3DGSNovel View SynthesisSurface Reconstruction

Mathematical Supplement for the $\texttt{gsplat}$ Library

2023-12-04 · Vickie Ye, Angjoo Kanazawa

This report provides the mathematical details of the gsplat library, a modular toolbox for efficient differentiable Gaussian splatting, as proposed by Kerbl et al. It provides a self-contained reference for the computati…

HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splatting

2024-02-09 · Zhenglin Zhou, Fan Ma, Hehe Fan, Zongxin Yang 외

Creating digital avatars from textual prompts has long been a desirable yet challenging task. Despite the promising results achieved with 2D diffusion priors, current methods struggle to create high-quality and consisten…

gsplat: An Open-Source Library for Gaussian Splatting

2024-09-10 · Vickie Ye, RuiLong Li, Justin Kerr, Matias Turkulainen 외

gsplat is an open-source library designed for training and developing Gaussian Splatting methods. It features a front-end with Python bindings compatible with the PyTorch library and a back-end with highly optimized CUDA…

Splatfacto-W: A Nerfstudio Implementation of Gaussian Splatting for Unconstrained Photo Collections

2024-07-17 · Congrong Xu, Justin Kerr, Angjoo Kanazawa

Novel view synthesis from unconstrained in-the-wild image collections remains a significant yet challenging task due to photometric variations and transient occluders that complicate accurate scene reconstruction. Previo…

3DGSNeRFNovel View Synthesis